pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian...

44
1 - 30 April 2017. Vol 4 Issue 3. For Private Circulation Only pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian Economy – Trend Indicators pg 37. PhillipCapital Coverage Universe – Valuation Summary

Transcript of pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian...

Page 1: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

1 - 30 April 2017. Vol 4 Issue 3. For Private Circulation Only

pg 32. INTERVIEW – Ms ANU ACHARYA

pg 35. Indian Economy – Trend Indicators

pg 37. PhillipCapital Coverage Universe – Valuation Summary

Page 2: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

3GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 2

1st March 2017 Issue 2 1st February 2017 Issue 1

1st December 2016 Issue 9

1st September 2016 Issue 7

1st November 2016 Issue 8

1st July 2016 Issue 6

VOL 4. ISSUE 3. 1 - 30 APRIL 2017

Vineet Bhatnagar- Managing Director and CEO

EDITORIAL BOARDNaveen Kulkarni, Manish Agarwalla, Kinshuk Bharti Tiwari, Dhawal Doshi

COVER & MAGAZINE DESIGN Chaitanya Modak, www.inhousedesign.co.in

EDITORRoshan Sony

RESEARCHBanking, NBFCs

Manish Agarwalla, Pradeep Agrawal, Paresh JainConsumer

Naveen Kulkarni, Jubil Jain, Preeyam ToliaCement

Vaibhav AgarwalEconomics

Anjali Verma, Shruti Bajpai Engineering, Capital Goods Jonas Bhutta, Vikram RawatInfrastructure & IT Services

Vibhor Singhal, Shyamal DhruveLogistics, Transportation & Midcap

Vikram SuryavanshiMidcap & Database Manager

Deepak AgarwalMedia

Manoj BeheraMetals & Automobiles

Dhawal Doshi, Nitesh Sharma, Yash DoshiOil & Gas

Sabri HazarikaHealthcare & Speciality Chemicals

Surya Patra, Mehul ShethTelecom

Naveen Kulkarni, Manoj Behera

EQUITY STRATEGYNaveen Kulkarni, Aashima Mutneja

TECHNICALSSubodh Gupta

PRODUCTION MANAGERGanesh Deorukhkar

SR. MANAGER - EQUITIES SUPPORTRosie Ferns

FOR EDITORIAL QUERIESPhillipCapital (India) Private Limited

No. 1, 18th Floor, Urmi Estate, 95 Ganpatrao Kadam Marg, Lower Parel West, Mumbai 400 013

SALES & DISTRIBUTION Ashvin Patil, Shubhangi Agrawal, Kishor Binwal,

Bhavin Shah, Ashka Gulati, Archan Vyas

CORPORATE COMMUNICATIONS Zarine Damania

[email protected]

Ground View - Previous Issues

Page 3: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

3GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 2

35 . Indian Economy: Trend Indicators

37. PhillipCapital Coverage Universe Valuation Summary

CONTENTSLetter from the MD

32. INTERVIEW: Ms Anu Acharya

CEO of Mapmygenome

4. COVER STORY: INDIAN MODERN RETAIL 2.0: GETTING DOWN TO BRASS TACKS

The Indian grocery retail landscape has changed

tremendously over the last two decades. The advent of

modern retail and ecommerce has led to a paradigm shift

in the shopping habits of many Indian customers. These

models continue to grow faster than the market, as they

offer more convenience, wider product assortment, home

delivery (in case of ecommerce), and cheaper prices.

Indian consumers have been the ultimate winners and the

average Indian consumer today is more spoilt for choice

than ever.

However, the secular revenue growth seen by Indian

modern retailers in the past decade has not translated into

sustainable profitable growth for the sector. Most remain in

the learning phase and continue to fine-tune their business

models and experiment with them, in their quest for the

secret mantra to crack Indian retail. However, some models

(such as D-Mart’s) have demonstrated initial success

and seem to have cracked the success mantra. D-Mart’s

successful listing has once again brought Indian retail

on investors’ radars, and it is imperative to understand if

Indian retail has finally come of age.

Our cover story ‘Indian Modern Retail 2.0: Brass Tacks?’

penned by analysts Jubil Jain and Preeyam Tolia, explores

the different kinds of modern retail business models in

India and the inherent strengths needed to succeed in a

competitive market like ours.

Also read in this issue – an interview with Ms Anu

Acharya, CEO of Mapmygenome, where she talks about

opportunities in the molecular/genetic diagnostics industry

and how “Precision Medicine” can become the future of

molecular diagnostics.

Best wishes

Vineet Bhatnagar

Page 4: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

5GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 4

COVER STORY

BY JUBIL JAIN & PREEYAM TOLIA

pg. 6 INTRODUCTION The curious case of Indian retail..._____________________________________pg. 11 ORGANISED RETAIL IN INDIA The rise and fall and rise_____________________________________pg. 16 INDIAN MODERN RETAIL INDUSTRY Which models are best poised to succeed?_____________________________________pg. 23 GLOBAL MODERN RETAIL INDUSTRY How are the world’s top modern retailers placed? _____________________________________pg. 28 ONLINE GROCERY IN INDIA Is it a threat to modern retail?_____________________________________

Page 5: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

5GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 4

D-Mart’s explosive market debut could be the start of something…

Dalal Street recently saw the listing of one of the most successful IPOs in recent times – D-Mart.

The company is a play on the fast-growing modern retail space in India. D-Mart’s stock listed

at Rs 604, netting gains of more than 100% on an issue price of Rs 299. Investor confidence

in D-Mart seems well founded if one considers its strong growth trajectory and the perceived

superiority of its business model vs. unsuccessful retail models in India. However, it is not

just D-Mart, but the entire retail pack that has captivated the investor community recently.

In the last year, most retail stocks have generated returns of more than 15%, with some far

higher, hinting at either excessive exuberance or an inflexion point in the growth trajectory for

organised retail in India.

Stock One-year stock return as on

30th April 2017

Trailing one year sales

growth

Trailing one year

EBITDA growth

D-Mart *22.5% 36% 54%

V2 Retail 276% 45% 10%

V-Mart 73% 16% 17%

Future Retail **117%

Trent 47% 15% 41%

Titan 32% 4% 5%

Aditya Birla Fashion and Retail 17%

Bata -1% 3% -4%

Shoppers Stop -6% 10% 7%

Indian retail stocks are in a strong bull run

*D-Mart was listed only on 21st March, 2017 and hence returns are calculated from that date**Future Retail was listed on 29th August 2016 and hence returns are calculated from that dateSource: Company, Bloomberg, PhillipCapital India estimates

Indian retail stocks are on a gravity-defying rally – déjà vu?

…but the last retail bull-run did not end on a happy note

This is not the first time that Indian retail counters are exploding on the ticker. In 2005-08,

many retail stocks (such as Pantaloons Retail and Vishal Retail) gave returns in excess of 100%

within a few months. However, back then, it did not end well for most retail companies – by

2009, most stores of Vishal Retail were closed down due to misallocation of capital by its

management; it was eventually sold to investors in 2011. Similarly, reeling under skyrocketing

debt, Future Group was forced to sell its Pantaloons chain to the Aditya Birla Group in 2012.

Another prominent retail company, Subhiksha, which had deferred its IPO indefinitely in

December 2007 in anticipation of better market conditions, was forced to close all its stores in

2009 due to capital mismanagement.

What makes a retail model successful and what leads to its possible doom? In this Ground

View, we attempt an in-depth analysis of different business models that exist in the Indian

modern retail space and try to determine, through global examples, ground research, and

existing literature, which business models are best poised to succeed in India.

Page 6: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

7GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 6

INTRODUCTION

The curious case of Indian retail...

Huge, but in a league of its ownThe Indian retail industry is one of the world’s largest

at US$ 616bn and is likely to achieve 12% CAGR

to touch US$ 960bn by 2020, as per Technopak.

It has multiple levers of long-term growth such as

favourable demographics, low penetration of various

consumption categories, and rising aspirations due

to economic growth and urbanisation.

While the Indian retail industry may be as big as the

retail industries in the world’s leading economies,

the Indian landscape is very different from most of

its emerging and developed-market peers. As per

AC Neilsen, the Indian market is highly fragmented

with 15mn retail outlets (mostly small mom-and-pop

stores) operating across the country. This translates

to 11 outlets per 1,000 people – one of the highest

retail densities in the world.

Countries *Retail store density per ‘000

people (2012)

Total no. of retail stores (in mn)

*Retail sales per capita (USD PPP)

*Total population (mn)

Retail sales per store (USD PPP)

Share of organised sector in retail

(2012)

US 3 0.94 7700 314 2,566,667 85%

UK 5 0.32 7500 63 1,500,000 80%

Malaysia 5.5 0.16 1500 29 272,727 55%

Thailand 18 1.26 2000 70 111,111 40%

China 3.5 4.73 1200 1350 342,857 20%

South Korea 11 0.54 3500 49 318,182 15%

Indonesia 12 2.89 800 241 66,667 25%

Philippines 9.5 0.91 1200 96 126,316 35%

India 12 15.12 500 1260 41,667 5%

*Research paper by marketing-trends-congress.com,

Source:Population Research Bureau, PhillipCapital India estimates

Global retail markets at a glance

With 15mn retail outlets, India has one of the highest retail densities (11 outlets per 1000 people) in the world

Page 7: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

7GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 6

Retail categories in India

Share of Indian retail

industry in 2016

Share of category sales

through organised retail

in 2016

Food & Grocery 67% 3%

Apparel & Accessories 8% 22%

Footwear 1% 27%

Jewellery & Watches 8% 25%

Pharmacy & Wellness 3% 10%

Consumer Electronics 6% 10%

Home & Living 4% 40%

Others 3% 12%

Retail categories in India

Source: Technopak Research & Analysis

Source: McKinsey & Company

Modern retail has the lowest levels of penetration in India vs. that in major emerging and developed markets

There are many factors that contribute to the

continued control of small retail outlets on India’s

retail landscape.

Ü The average Indian consumer prefers

smaller SKUs: Unlike consumers in other

major retail markets, which prefer purchase

of larger SKUs due to significant cost savings,

the average Indian consumer tends to prefer

smaller SKUs due to the lower cash outlay

involved. An example – HUL brand Clinic

Plus’ one-rupee shampoo sachet has been its

largest selling SKU in its hair care portfolio for

a very long time. Small SKUs dominate sales

of many FMCG and grocery categories, and

account for a sizeable share of revenue for

most FMCG companies. As modern trade

normally offers discounts only on larger SKUs,

and offers no benefit to buyers of small SKUs,

most customers prefer to buy from local outlets

due to convenience, availability of credit, and a

personal relationship.

Ü Higher population density: India’s population

density, at 441/sq. km, is significantly higher

than what it is in emerging and developed

peers. The population density is even higher in

Indian metros and tier-1 cities vs. other global

cities. This kind of density, combined with

consumer preference for local retail outlets,

makes multiple retail outlets in the same

locality, selling the same category of goods,

financially viable.

Mom-and-pop stores rule the marketIn India, organised retail accounts for less than

10% of total retail sales, as per Technopak –

demonstrating the dominance of smaller retail

outlets. In contrast, the share of modern retail in

emerging markets such as China, Indonesia, and

Philippines is far higher at 20%, 25%, and 35%.

Under-penetration of organised retail is more striking

in the foods and grocery segment (modern retail)

which dominates retail spending in India (c. 67%).

Just 3% of sales in foods and grocery categories are

through organised retail (as per Technopak), putting

India at the very bottom in modern retail penetration

globally.

Page 8: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

9GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 8

Country Per sq km

India 441

Brazil 25

China 146

Japan 348

United Kingdom 269

United States 35

Metropolitan region Per sq km

Mumbai 4,764

New Delhi 6,038

Kolkata 7,480

Shanghai 3,809

Beijing 1,322

New York 688

London 1,656

Tokyo 2,785

Source: Census 2011, Shanghai Bureau of Statistics, Beijing Bureau of Statistics, U.S. Census Bureau, Eurostat, Tokyo Metropolitan Government

Source: World bank

Countrywise population density in 2015

Citywise population density in 2015

Ü Government regulations have hindered the

entry of global retail giants while local modern

retail is still in a learning phase: India was closed

to global retailers for a long time. It only opened

itself in 2012 when the government allowed 51%

FDI in multi-brand retail. As a result, many global

retail chains such as Walmart, Target, Aldi, and

Seven Eleven, present in most major economies,

are absent from the Indian retail landscape –

though some have recently tied up with Indian

companies for B2B retail. Also, Indian organised

retail players are still in a learning phase – with

many players still struggling to find a profitable

and sustainable business model. As a result,

competition for unorganised retailers in India is

very limited vs. that in other countries.

Ü Lack of well-paying jobs and comparatively

lower wages make retailing attractive: The per

capita income in India (around US$ 7,200 in PPP)

is far lower than that in emerging and developed

peers, and below the global average of US$

15,500, as per IMF. While an unskilled Indian

labourer earns just Rs 5,000-10,000 per month,

even a semi-skilled Indian worker makes only Rs

10,000-20,000 per month in most Indian cities.

In contrast, a retailer with a 100 sq. ft. shop on

rent can make around Rs 20,000 per month, with

an initial investment of Rs 250,000 and working

Three retail outlets with a very similar product assortment existing side by side on on a street in Andheri, a bustling Mumbai suburb

Page 9: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

9GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 8

capital of Rs 170,000. Due to lower wages and

lower employment opportunities for well paying

jobs, many people in the workforce in India

prefer retailing, which provides stable income,

independence, and self-satisfaction. Retailing

becomes even more attractive and profitable

in a country like India with very high property

ownership rates (866 per 1,000 households as

per 2011 census) as it eliminates rental expenses.

This can increase monthly earnings by up to Rs

8,000 - 10,000.

(All values in Rs) Rented shop Owned shop

Sales 3,600,000 3,600,000

Retailer’s margin 10% 10%

COGS 3,240,000 3,240,000

Gross Profit 360,000 360,000

Rent 100,000 -

Employee costs - -

Other expenses 30,000 30,000

Total operating expenses 130,000 30,000

EBITDA 230,000 330,000

Depreciation - -

Tax - -

PAT 230,000 330,000

Monthly income 19,167 27,500

Inventory 300,000 300,000

Payables 150,000 150,000

Receivables 19,726 19,726

Working Capital required 169,726 169,726

Initial Capital Investment required - Furniture and fixtures

250,000 250,000

Financials of average grocery store (100 sq. ft.) in an Indian metro

Source: PhillipCapital India estimates

Mom-and-pop stores dominate the industry as they offer convenience of location, credit and quick transactions

However, organised retail is poised to grow faster While organised retail contributes to less than 10%

of the total retail sales in India, it is growing faster

than the overall retail industry. Mom-and-pop outlets

tend to dominate the Indian retail industry as they

offer convenience of location, credit, and a quick

shopping experience. However, organised retail

outlets have their own set of strengths, which make

them a very attractive shopping destination for

value-conscious and brand-savvy customers. These

outlets offer an expansive product assortment,

higher variety of brands, a one-stop shopping

destination for various needs, and the luxury of

shopping at leisure while browsing through sections

of various product categories.

Within organised retail in India, modern retail

(focused on the foods and grocery category) has the

lowest penetration (3%) and is widely estimated to

achieve 25% CAGR to touch US$ 31bn in 2020 from

US$ 13bn currently as per Technopak.

What differentiates organised chains from unorganised retailers is the significantly high rate of discounting offered by the former due to their economies of scale

Page 10: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

11GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 10

No. of outlets currently

Sales (FY16) (Rs bn)

EBITDA (FY16) (Rs bn)

Cumulative Free Cash Flow

(FY12-16) (Rs bn)

Debt/Equity FY16

Average SSSG (FY12-16)

Sales CAGR (FY12-16)

Reliance Retail 3353 185.5 9.1 3.2bn 0.2 NA 48%

Future Retail 738 72.7 0.9 -40.6bn 0.6 9%

D-Mart 118 85.9 6.6 -6.3bn 0.8 25.40% 40%

Spencers Retail 124 18.6 -0.6 -5bn 13 11.60% 12%

Hypercity 19 9.8 -0.25 -2.2bn 119 NA 6.30%

Grocery shopping Small retail outlets Organised chains

Convenience ü Close location, quick transactions û Distant location, shopping takes time

Credit availability ü Yes û No (but allow payment through credit cards)

Product assortment û Limited brands and categories, small SKUs available ü Wide, one stop shopping solution, small SKUs may not be available

Shopping style û Over the counter in limited time ü Browse through various product sections at one’s own pace

Pricing structure û MRP ü Discounts available

Small retail outlets and organised chains target different needs of consumers

Financial and operational parameters of key Indian modern retail players

Indian modern retail is still in the learning phase Modern retail in India is a fast-growing industry with

most players reporting significant revenue growth.

However, this has not translated into substantial

profits. Most current Indian modern retail players

suffer from structurally low margins, very high debt

levels, and consistently negative free cash flows. The

Indian modern retail industry is still in the learning

phase and its search for sustainability is still ongoing.

As a result, no modern retail company in India has

the substantial size and scale that can be seen in the

developed world.

Most Indian modern retail players suffer from structurally low margins, very high debt levels, and consistently negative free cash flows

Source: Company. PhillipCapital India estimates

Page 11: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

11GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 10

ORGANISED RETAIL IN INDIA

The rise and fall and rise

A brief historyStandalone modern retail outlets and big departmental stores have existed in most large Indian

cities for many decades. Some, like Akbarallys in Mumbai, are more than a century old. However,

organised retailing in India took off only in the 1990s – when the first fashion retailing chains

opened (Shoppers Stop in 1991 and Pantaloons in 1997). At around the same time, the first

organised grocery retailing chains started sprouting (Subhiksha in 1997, Spencers in 1990s,

and Big Bazaar in 2001). The formats varied significantly across chains, even within the same

categories – while Big Bazaar was a large hypermarket store (30,000 sq. ft.) with a focus on

range, Subhiksha was a small-format grocery super market (1,000-5,000 sq. ft.) with a focus on

value. Most organised retail chains were highly successful and saw their turnover and outlet

count rising manifold in a decade.

The golden age of organised retailing in India (2000-07)This period saw very strong growth in footfalls and

sales for most organised retail chains in India. For

most, growth was driven by a strong focus on the

front-end of their business, i.e., the consumer-facing

aspect. Most of these retailers offered significant

discounts to customers and were able to generate

healthy footfalls and sales based on their value

Organised Retail chains

Sales (Rs mn) EBITDA (Rs mn) Outlet count

FY03 FY07 FY10 FY03 FY07 FY10 FY03 FY07 FY10

Future Retail 4448 33928 66614 374 2156 5921 12 Pantaloons19 Big Bazaar

31 Food Bazaar0.6mn sq. ft.

31 Pantaloons56 Big Bazaar

86 Food Bazaar5.2mn sq. ft.

48 Pantaloons132 Big Bazaar

185 Food Bazaar123 KB’s Fair Price

13.2 mn sq. ft.

Vishal Retail 500 6026 11054 -15.2 680.1 -4600 14 541.2mn sq. ft.

17178000 sq. ft

Subhiksha 2085 8255 27.5 258.2 ~130 ~900 ~1600

Transition of key organised chains during (FY03-10)

proposition. Subhiksha, a prominent grocery chain,

offered average discounts of 8% on various grocery

categories. In spite of this, most retailers made

satisfactory operating margins due to cost control

and economies of scale in procurement. While the

free-cash flow was still negative for most, it was not

a big concern due to the small business size and

manageable debt levels. Consensus expectations

of exponential future growth for many retailers led

to their stock prices delivering phenomenal returns

during that time.

Source: Company, PhillipCapital India estimates

Page 12: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

13GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 12

Stock price movement of Future Retail vs. SENSEX (base 100 as on 1st Jan 2002)

Stock price movement of Vishal Retail vs. SENSEX (base 100 as on 4th July 2007)

The Indian organised retail story fizzles out (2007-10)While a strong focus on the front-end helped

achieve significant growth in footfalls and same-store

sales for organised retail chains in India, a lack of

focus on the back-end proved disastrous for them

as they engaged in aggressive expansion plans in

2007-10. Most, overconfident due to the growth

they saw in 2000-07, more than doubled their store

count in 2007-10 through debt without improving

systems and processes. In spite of strong growth in

sales in 2007-09, ever-increasing inventory levels and

unmanageable debt forced retailers such as Vishal

Retail and Subhiksha to default on loan payments

and shut shop in 2009. Future Retail’s Pantaloon

chain, marred by skyrocketing debt levels, was sold

to the Aditya Birla Group in 2012.

So what went wrong?

Ü Organised Indian retailers bit off more than

they could chew: Significant growth in sales in

2002-07 emboldened Indian retail companies to

pursue very aggressive growth strategies. Kishore

Biyani-led Future Group increased Big Bazaar/

Pantaloons outlets by 100%/40% in FY07-09.

Similarly, Subhiksha more than tripled its outlet

count to 1600 in FY07-09, and Vishal Retail also

expanded aggressively. While SSSG and operating

margins remained strong during the period, EBITDA

generated was far lower than that required to fuel

capex or meet working-capital requirements. This

pushed companies into a debt spiral.

In spite of their strong growth in sales in 2007-09, for major retailers of that time, ever-increasing inventory and unmanageable debt derailed their growth story completely

Future Retail

Retail companies delivered phenomenal returns till 2007 but the rally fizzled out laterSo

urce

: ACE

Equ

ity

Sour

ce: A

CE E

quity

, Phi

llipC

apita

l Ind

ia E

stim

ates

Page 13: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

13GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 12

Debt/Equity ratio of retail companies

Vishal Retail Sales growth, SSG and EBITDA growth for Future Retail

Subhiksha

Ü Expansion over efficiency spelled disaster: For

most companies, expansion accelerated from

2007, despite a weak understanding of inventory

management – this led to significant increases in

inventory levels. For Vishal Retail, inventory days

increased to 169 in FY09 from an average 70 in 2004-

06. These increases led to drastically higher working

capital requirements, which forced companies further

into debt. Due to rising debt levels, companies had

to increase cost controls to up their margins, which

meant lower discounts at their outlets. This led to an

even more pile up of undesirable inventory, which

ultimately led to defaults.

Inventory days for key retailers

Sour

ce: B

loom

berg

, Ace

Equ

ity, P

hilli

pCap

ital I

ndia

Res

earc

h Es

timat

es

Page 14: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

15GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 14

Indian organised retail 2.0 (2011-present)

Lessons from the past

The Indian organised retail landscape has taken

a decisive turn since 2011 after Shubhiksha’s

bankruptcy and sell-offs of Vishal Retail and

Pantaloons chains. Current organised retail players

in India have learnt from mistakes – their own and

those committed by their peers. They are more

focused on sustainability and profitability. The

business models have become more agile and can

withstand shocks better.

Slow and steady wins the race

Most present Indian retail chains increase retail

space by only around 10-15% annually vs. the 50-

100% increases seen in the furious growth period

of 2007-10. V2 Retail vs. Vishal Retail is a great

example of this evolved approach. Mr Ram Chandra

Agarwal, founder of Vishal Retail, launched V2 Retail

after the distress sale of his chain Vishal Retail in

2012. V2 Retail works with a very different strategy

vs. Vishal Retail. It operates stores of about 10,000

sq. ft. and adds 60,000-70,000 sq. ft. annually. In

comparison, Vishal Retail operated 18,000 sq. ft.

stores and used to add 1mn sq. ft. of retail space

annually during its heydays in 2007-09.

Current Indian organised retailers have begun to place a huge emphasis on sustainability and profitability over scale

(mn sq. ft.) FY12 FY13 FY14 FY15 FY16

D-Mart 1.55 1.76 2.14 2.66 3.33

Big Bazaar 7.99 7.98 7.62 8.68 *8.98

Spencers 1 0.88 1.08 1.05 1.08*As on 31st December 2015

Retail space expansion of major modern retail chains during FY12-16

FY09 FY16

Future Enterprises 88 42 (in FY15)

Vishal Retail 170 103 (in FY16)

V-Mart 108 87

Shoppers Stop 43 36

Subhiksha 75 (in FY07)

D-Mart 28 23

Spencers 35.6

Inventory days comparison for key retail chains

Using technology for leaner operations

Currently, most organised retail chains operate

at significantly lower inventory levels vs. that in

2007-10. They exert control over their inventory

levels by focusing on product assortment, avoiding

illiquid products, ordering fast-moving products,

and minimising inventory build-up through various

corrective actions such as stock returns, discount

sales, and shifting inventory to other stores.

In the last decade, IT systems have played a key role

in significantly improving inventory management.

Most companies now operate their entire supply

chain using advanced IT systems. For example,

D-Mart uses IT systems for procurement, sales, and

inventory management. The IT systems help it to

identify and quickly react to changes in customer

preferences by adjusting products available, brands

carried, stock levels, and pricing in each of its

stores, and effectively monitoring and managing the

performance of each store.

Source: Company

Source: Company

Page 15: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

15GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 14

Entering a period of maturity

Indian organised retail has finally started

maturing

The Indian organised retail industry is in a far more

sustainable and mature phase than it was a decade

ago. While current investors may not expect the

exponential growth and phenomenal stock returns

from incumbent organised retailers (as seen a

decade ago), they will be far more confident about

the quality of growth and sustainability of business

models, at least for a few of the present retailers.

In the modern retail space, some chains (such as

D-Mart) have been able to develop retail models

that are profitable and sustainable, and have been

able to recreate the same success in each new store

that they open.

FY1975 FY1990 15 year CAGR

Walmart

Sales (US$ mn) 236 25,811 36.7%

PAT (US$ mn) 6.4 1,076 40.8%

No. of stores 104 1525 19.6%

Stock price 100 (1975 value as base)

14,740 39.5%

Potential stock price in 1975 to provide 20% annual returns during FY1975-1990 947

Potential stock price in 1975 to provide 25% annual returns during FY1975-1990 510

In hindsight, what would Walmart’s correct valuation be in 1975?

Successful retailers will be able to (justifiably) command a significant valuation premium

While the story of modern retail in India has just

about started, there is huge scope for growth

through market-share gains from unorganised

retailers. Successful retailers that have the ability to

successfully copy-paste their models in their new

stores, will see exponential levels of (sustainable

and profitable) growth and will be highly valued by

investors.

Walmart (founded in 1962) was at a similar stage in

1975 compared to present day D-Mart (started in

2003). Walmart’s sales/PAT CAGR was 37%/41% in

1975-90 and its stock grew 40% annually in the same

period. An investor, confident of Walmart’s ability of

delivering 41% PAT growth for next 15 years, could

have purchased Walmart’s stock at five-times its actual

price in 1975 and would have still earned 25% annual

return on the stock for the next 15 years.

Source: Walmart, Bloomberg

An investor, confident of Walmart’s ability of delivering 41% PAT growth for next 15 years, could have purchased Walmart’s stock at five-times its actual price in 1975 and would have still earned 25% annual return on the stock for the next 15 years.

Page 16: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

17GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 16

INDIAN MODERN RETAIL INDUSTRY

Which models are best poised to succeed?

D-Mart – On the right pathSupermarket model with focus on value and sustainable

expansion

D-Mart was started by India’s legendary investor-turned-

entrepreneur Radhakishan Damani in 2003. It is now a major

retail chain in India with 118 stores, 87 of which are located

in the western Indian states of Maharashtra and Gujarat.

Through a strategy called EDLP (everyday low prices), which

is also followed by Wal-Mart, D-Mart has created a niche

for itself in the modern retail space in India. Customers

value it for its relatively low pricing across all major product

categories, the whole year round. Because of its strong value

focus and ability to offer lowest prices to consumers, its sales

CAGR in FY12-16 was

high at 40% to Rs

86bn.

While being a leader

in brick and mortar

retail, the company

has its share of admirers in the ecommerce world too. In a

recent email to the employees of Indian e-commerce giant

Snapdeal, its founder Kunal Bahl asked the employees to

follow the example of D-Mart in how to run the business.

He reckoned that D-Mart’s focus on unit-level profitability

and core audience helped it to deliver phenomenal results.

He also remarked that unlike other retail companies, which

prioritise expansion over profitability, D-Mart succeeded by

doing just the opposite.

Right mix of global retail giants Walmart and Costco

D-Mart is one of the few retail chains in India that has been

able to crack the secret of profitability and sustainability in

a business model in Indian retail. It operates large-format

stores (about 30,000 sq. ft.) and like Wal-Mart, prefers to own

the stores or rent them on very long-term leases. However,

unlike Wal-Mart, it does not offer an expansive array of

brands in each category. Instead, like Costco, it offers a very

limited product assortment of fast-selling SKUs, which helps

it to keep a tight control on inventory and increase inventory

turns.

Growth, but not at the cost of worsening financials

D-Mart has a very conservative policy on new store openings

and prioritises sustainability and profitability over scale. It

opens 70% of new stores in existing geographies and is

very cautious about entering new geographies. This has

helped it to have a better understanding of its customers

and catchment areas, and to fine-tune its sales strategy.

Because of D-Mart’s focus on operating cost control and

tight inventory management, its last four-year EBITDA/PAT

CAGR was 48%/52% to touch Rs 6.6/3.2bn. Its focus on

sustainability has helped it to maintain working capital, debt/

equity, and return

ratios at healthy

levels.

D-Mart is present

only in 45 cities

in India, and if it

is able to maintain its focus on sustainable and profitable

growth, it can cover 250-300 cities in the long term – thereby

increasing its store count, sales, and profits exponentially. At

a market capitalisation of Rs 45bn, it is the most expensive

listed retail chains in India. It is likely to grow significantly

larger in the long term if it continues to pursue the right

strategies.

Like Walmart, D-Mart offers low prices every day, and prefers to own stores or rent them on a long-term lease. Like Costco, D-Mart offers a limited product assortment and keeps inventory under control

FY12 FY13 FY14 FY15 FY16

No. of stores 55 62 75 89 110

Area (mn sq.ft.) 1.55 1.76 2.14 2.66 3.33

Sales (Rs mn) 22,034 33,330 46,756 64,247 85,655

SSSG 20.3% 31.6% 26.1% 22.4% 21.5%

Ebitda (Rs mn) 1,380 2,150 3,418 4,590 6,635

Key financial parameters of D-Mart

Source: Company

Page 17: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

17GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 16

FY12 FY13 FY14 FY15 FY16

No. of stores 1,282 1,466 1,691 2,621 3,245

Area (mn sq.ft.) 9.0 11.7 12.5 12.8

Sales (Rs mn) 75,990 108,000 144,960 176,400 216,120

EBIT (Rs mn) -342 780 3630 7840 8910

In FY13-16, Reliance Retail’s sales/EBIT CAGR was 26%/123%

With a network of 3,553 outlets across 686 cities and a pan-

India retail footprint of over 13.25mn sq. ft, Reliance Retail is

India’s largest retail company. Reliance Fresh, started in 2006,

is Reliance Retail’s supermarket grocery chain. It operates

around 500 stores (average area 5,000-10,000 sq. ft.) across

80 cities in India. It is positioned on freshness and savings

with the core promise of Fresh Hamesha, Available Hamesha,

and Savings Hamesha (Hamesha = Always). Unlike other

grocery chains, which offer discounts on certain brands of

products in certain categories, Reliance Fresh offers blanket

discounts of 2-5% on all brands within most categories.

Reliance Retail also includes chains like Reliance Market

(cash-and-carry; 37 cities with 2.5mn members), Reliance

Digital (electronics; 1,900 stores), Reliance Trends (fashion;

320 stores in 177 cities), Reliance Footprint (footwear), and

Reliance Jewels (jewellery; 50 stores in 36 cities).

Reliance Retail – India’s largest

Spencer Retail, part of RP Sanjiv Goenka Group, is a major

Indian multi-format retail chain with 120 stores including

37 hyper-stores in over 35 cities in south and north India.

Spencer’s hypermarkets are some of the most expansive

retail stores in the country with the area of many outlets in

excess of 25,000 sq. ft. Unlike D-Mart, which has a limited

product assortment, Spencer’s hypermarkets offer one of

the widest assortment of brands – this is one of the key

differentiators for Spencers according to its website. It also

has smaller-format stores under Spencer Supermarkets (17)

Spencer Retail – Not yet profitable

Unlike other grocery chains, which offer discounts on certain brands of products in certain categories, Reliance Fresh offers blanket discounts of 2-5% on all brands within most categories

Spencer’s hypermarkets are some of the most expansive retail stores in the country with a very wide product assortment

Big Bazaar is India’s largest hypermarket chain with 231 outlets

with per store area of 3,000-5,000 sq. ft. and Spencer Dailies

(68) with per-store area of less than 3,000 sq. ft.

During FY12-16, same-store sales for Spencers grew annually

by 11% and total sales grew by 11%. However, the chain

is still not profitable; it reported a loss of Rs 530mn at the

EBITDA level in FY16.

FY12 FY13 FY14 FY15 FY16

No. of stores 182 131 128 126 118

Area (mn sq.ft.) 1 0.88 1.08 1.05 1.08

Sales (Rs mn) 11,990 13,378 14,513 16,660 18,591

SSSG 14.7% 17.8% 7.7% 9.4% 8.4%

Ebitda (Rs mn) (1,477) (872) (768) (733) (596)

Key financial parameters of Spencer Retail

Future Retail is one of the most prominent and oldest retail

companies in India and operates through its chains Big

Bazaar, Easy Day, Food Bazaar, and others. Big Bazaar is

India’s largest hypermarket chain with 231 outlets and a

total area of 9.8mn sq. ft., across 124 cities. Big Bazaar is a

multi-category large-format chain with a typical store size

of 30,000-40,000 sq. ft. Future Retail also operates other

smaller formats like Easy Day (neighbourhood stores chain)

with 379 outlets across 128 cities, FBB (a fashion chain) – 54

standalone stores, Foodhall – 6 stores, ezone – 87 stores, and

HomeTown – 37 stores.

While Future Group was one of the first movers in the Indian

retail space through its chains Pantaloons and Big Bazaar, it

faced skyrocketing debt due to aggressive expansion and

capital misallocation. As a result, it hived off Pantaloons and

sold it to Aditya Birla group in 2012. During FY12-16, its

SSSG CAGR was 7.2% annually for its value retail portfolio

(Big Bazaar and Food Bazaar).

Future Retail – The first-mover

Source: Company

Source: Company

Page 18: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

19GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 18

GROUND VIEW

GOES SHOPPIN

G

Selling price for some standard grocery items at key retail chains

D-Mart – Central Mumbai

Ü Bustling with activity even on Monday

evening

Ü Air-conditioned modern retail store,

visited by all economic sections (lower

to high) primarily due to its value

proposition

Ü Minimalistic interiors, plain aesthetics,

narrower lanes vs. other chains such as

Spencer or Big Bazaar

Ü More than compensates for dull interiors

through the huge discounts that it

provides vs. others – these ranged from

5-15%, and are available on multiple

brands in almost all categories every day

Ü Surveyed customers indicated that they

save Rs 500-1000 per month on grocery

bills by shopping here

Ü Discounts offered on grocery items

(fruits, vegetables, and grains) were

lower to nil vs. those on branded

products

(All prices in Rs) MRP D-Mart Price

Big basket.

com

Big Bazaar

Spencer Reliance Fresh

Packaged Foods

Good Day 200g 35 31 35 35 35 33.3

Bourbon 150g 27 24 27 27 23.3 25.7

Maggi (pack of 6) 67 61 67 67 65.7

Soap

Lux 3x150g 105 98 105 105 105 103

Lifebuoy 4x125g 100 93 100 100 100 100

Detergent

Surf Excel 1.5kg 187 172 187 187 162 183.3

Rin 2kg 150 140 150 150 150 147

Ariel 1kg 199 187 199 199 169 195

Toothpaste

Colgate Total 140g 105 95 105 105 92 99.8

Colgate Dental Cream 300g

134 116 134 134 113 127.3

Dabur Red 200g 90 75 90 90 82 85.5

HFD

Horlicks 500g 240 230 240 240 240 235.2

Bourvita 1kg 395 340 395 395 395 387.1

Horlicks 1kg 446 446 425 446 446 446

Source: PhillipCapital Groundview checks

Page 19: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

19GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 18

GV talked to a shopper Mr Kadam about why he shops at D-Mart. He said, “I stay at Kanjurmarg East but travel every week to this store in Kanjurmarg West as it offers the lowest prices for all my grocery needs and helps me save around Rs 1000 per month. I even know of some shopkeepers in my area who buy goods for sale from D-Mart.”

GV asked one of the storekeepers Miss Rathi about why consumers buy from Big Bazaar and not from nearby grocery outlets. She said, “People come to malls (Big Bazaar) for variety. It offers a huge range of brands, cheap ones as well as expensive ones, and young salaried people shop 15 days to 1 month worth of groceries in one go here.”

Big Bazaar – South Mumbai

Ü Larger than D-Mart or Star Bazaar stores in similar neighbourhoods

Ü Around 60% of space was reserved for grocery and 40% for general merchandise such as apparel

Ü Footfalls were fairly strong on a Tuesday evening

Ü Better store aesthetics, wider lanes, wider product assortment as compared to D-Mart

Ü Had lower discounts compared to other retail chains (Big Bazaar does not offer high discounts every day but

offers huge discounts on few special days in a year)

Page 20: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

21GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 20

When asked what differentiates Spencers, the store manager said, “Our hypermarkets are positioned on range and variety. People come to our stores for the quality, price, and exotic brands of products – they will not find these in other stores. We also offer discounts on various product categories, which helps customers save money.”

Spencers Hypermarket – Gurgaon

Ü The stores were relatively less crowded vs. D-Mart or Big Bazaar on a Monday evening

Ü Majority of the customers seemed to belong to upper- or upper-middle-class economic groups

Ü Store aesthetics and ambience were better than other chains – widest lanes between product racks

Ü Had the widest assortment of brands in most categories

Ü Prices of most products in the store were higher than those in D-Mart or Reliance Fresh, but comparable or lower

than Big Bazaar

Ü While Spencers has positioned itself as a hypermarket offering the widest assortment of products, it seemed that

in some of its categories (green tea, olive oil, noodles), it had more brands than what was optimum

Page 21: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

21GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 20

“Reliance Fresh stores are known for the quality of fruits, grains, and vegetables, and the guaranteed savings on MRP on each and every product” – Mr Ritwik, Store Salesman, Reliance Fresh, Gurgaon

Reliance Fresh – Gurgaon

Ü The store had strong footfalls on Monday evening

Ü The total retail area was around 10-12,000 sq. ft – minimalistic interiors and plain aesthetics

Ü Unlike other grocery chains that offer discounts on select brands in select categories, Reliance Fresh offers

blanket discounts of 2-5% on all brands in most categories

Ü This store was offering 2% discount on MRP for any category of product and an additional 3% off on select

categories such as biscuits and toothpaste

Ü While the savings in Reliance Fresh would be higher than Big Bazaar and Spencers, savings in D-Mart would be

highest for most shoppers due to higher discounts available on select products in each category

Ü The variety of brands in each product category was limited in Reliance Fresh, like in D-Mart

Ü Had products in various categories under own private label

Page 22: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

23GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 22

D-Mart and Reliance Fresh best poised to succeed, Big

Bazaar needs to work on value proposition, Spencers

Hypermarkets needs to work on efficiencies

D-Mart’s business model seems best poised for sustainable

and profitable growth. It offers lowest prices on most

product categories (which leads to higher footfalls and sales),

does not operate in expensive locations such as malls or

downtown areas of cities (which saves costs), and has tight

control on inventory due to limited product assortment

(which helps to reduce working-capital needs).

Like D-Mart, Reliance Fresh offers low prices, rarely operates

in malls, and has a limited product assortment. While its

financial details are not available publicly, we believe that

Reliance Fresh’s business model is sound and the chain can

grow sustainably by continuing to control inventory days

and operating costs, and not undertaking very aggressive

expansions.

While Big Bazaar outlets offer a wide product assortment

and the convenience of one-stop shopping for all daily

needs, it may lose footfalls to other retail chains due to its

inability to offer effective savings to customers on a daily

basis.

Spencers Hypermarkets seems to have scope to reduce

both costs and inventory. These stores are slightly ahead of

time - more expansive (area) and expensive (aesthetics) than

optimum. Also, the number of brands available at Spencers

Hypermarkets may be more than what is optimum.

Quick takeaways:

Ü Price: D-Mart offers the lowest prices for most branded

products, followed by Reliance Fresh, followed by Big

Bazaar/Spencers. A price-conscious customer will prefer

D-Mart over other stores in the same locality.

Ü Product assortment: Spencers Hypermarkets, followed

by Big Bazaar, offers a wider assortment of brands

compared to D-Mart and Reliance Fresh.

Ü Store size: Spencers and Big Bazaar have larger store

sizes, followed by D-Mart, followed by Reliance Fresh.

Ü Store aesthetics: Spencers Hypermarkets, followed by

Big Bazaar, have higher focus on aesthetics and ambience

compared to D-Mart and Reliance Fresh.

Ü Footfalls: D-Mart had the highest footfalls, followed by

Big Bazaar/Reliance Fresh, followed by Spencers.

Ü Store location: Most stores of Big Bazaar and Spencer

Hypermarkets were in malls, which have higher rentals.

Some stores of Reliance Fresh were in malls. No D-Mart

stores are in malls; they are always standalone buildings

What GV took away from shopping

Big Bazaar outlets in Mumbai

D-Mart outlets in Mumbai

Reliance Fresh – Mumbai

Spencers – NCR + Chennai

Mall 7 outlets Nil 1 outlet 3 outlets

Non-Mall 2 outlets 21 outlets 14 outlets 29 outlets

Location of modern retail outlets by chain

Source: Company, PhillipCapital India Estimates

Page 23: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

23GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 22

GLOBAL MODERN RETAIL INDUSTRY

Industry overview

Global retail industry reported sales of US$ 22.6bn in 2015 and is expected

to grow to US$ 28bn in 2019 (CAGR of 6%), as per market research firm

‘Research and Markets’. There is a huge variation in the structure of the

retail industries in different geographies – modern retail dominates in North

America and Europe, while traditional retail is more prevalent in Asia, Africa,

and South America.

Retail industry sales by channel in various regions

Source: The Neilson Company

Page 24: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

25GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 24

The word retail comes from an old French word tailler, which

means to cut off; the prefix ‘re’ means again. Over time, the

noun ‘retail’ meant to cut off smaller portions from large

lumps of goods and sell to consumers. Trading has been an

important part of human civilisation and has existed since

ancient times – earlier through the barter system or precious

stones, and later through money. In ancient and medieval

times, open air, public markets operated in town centres

in the civilised world throughout Rome, Greece, Babylon,

and India. In these markets, the sellers were mostly local

(peasantry) and sold or exchanged their surpluses for other

necessities or small luxuries. The markets also comprised of

a few (probably the very first) entrepreneurs who directly or

indirectly procured locally scarce or exotic goods from distant

places and sold locally for profits.

The retail landscape changed significantly with the onset

of the industrial revolution in Europe and the US. Industrial

revolution made possible the mass production and transpor-

tation of goods. It also increased urbanisation and created

a sizeable middle class, which worked in factories and no

longer possessed the facility to grow its own food. This led to

the emergence of high-street culture with fixed shops selling

multiple brands of single/multiple categories of goods to a

variety of consumers. Increasing prosperity and falling pro-

duction costs helped poor people to get access to goods,

which until now were only consumed by upper class.

Rising consumer culture and increasing prosperity gave way

to the opening up of the first departmental stores in the US

and Europe including – Harrod’s in London (1834), Le Bon

Marche in Paris (1852), and Macy’s in New York (1858). How-

ever, retail was never the same after the Walmart retail chain

opened its first store in 1962 in Arkansas, USA. This heralded

the era of modern retail. Walmart has since then opened

more than 11,000 stores in the US and across the world.

Today, modern retail dominates the US and European retail

industries, and has been among the fastest growing formats

in many developing economies such as India and China,

during the last decade. Globally, multi-national retail giants

such as Walmart, Target, Aldi, Tesco, and others dominate

the retail industry in most developed countries.

A brief history of retailing

Company Country Retail Rev (FY15) (US$ bn)

Retail Rev CAGR (FY10-15) (%)

Net Profit mar-gin (FY15) (%)

Countries present in

Wal-Mart Stores, inc. US 482 2.7 3.1 30

Costco Wholesale Corporation US 116 8.3 2.1 10

The Kroger Co. US 110 6.0 1.9 1

Schwarz Unternehmenstreuhand KG Germany 94 7.4 na 26

Walgreens Boost Alliance, Inc. (formerly Walgreen Co.) US 90 5.9 4.1 10

The Home Depot Inc. US 89 5.4 7.9 4

Carrefour S.A. France 85 -3.1 1.4 35

Aldi Einkauf GmbH & Co. oHG Germany 82 8.0 na 17

Tesco PLC UK 81 -2.3 0.6 10

Amazon.com, Inc. US 79 20.8 0.6 14

Top 10 global retailers - American and European firms dominate the global retail industry

Source: Companies, Deloitte

Page 25: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

25GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 24

Wal-Mart Stores, Inc Ü Started by Sam Walton in 1962

Ü World’s largest – an American multinational

retailing giant

Ü As of January 2017, it has 11,695 stores and

Sam’s clubs in 28 countries

Ü 90% of Americans live within 15 miles of a Wal-

Mart store

Ü In 2016, about 62% of Wal-Mart’s US$ 486bn

revenue came from its US operations

Ü Wal-Mart India owns and operates ‘21 Best Price

Modern Wholesale’ stores

Major global retail chains across the world

What differentiates Walmart?

Ü EDLP (everyday low price): Wall-Mart

pioneered EDLP since its first store in 1962, and

captured millions of customers worldwide. EDLP

is a pricing strategy that promises consumers that

they will get better and lower prices on products

than what competitors provide, without the need

to wait for promotions or price discounts

Ü Retail Link System (RLS): Wal-Mart

revolutionised the way retail companies manage

their supply chains in more ways than one.

Walmart’s RLS is one of the largest B2B supply

chain systems in the world and shares its vast

trove of real-time sales data and forecasts with its

largest suppliers that stock its shelves. This data

helps the suppliers to plan their production and

product delivery before stock-outs. The system

gives the supplier 100 weeks of product sales

history and tracks the product’s performance

globally. For example, Procter & Gamble set up

an inventory system with Wal-Mart that included

an automatic re-ordering process linking the

supplier and retailer. This system alerts P&G

when a product is running low at a store, which

in turn triggers an order for the nearest P&G

factory to ship the item to a distribution center

or directly to the store. For P&G, synchronising

its product data with Wal-Mart’s sales saved the

supplier millions annually. The goal is to master

the art of knowing what it needed, how much is

needed, and when it is needed.

ÜFocus on smaller towns: Wal-Mart’s focus is on

smaller towns instead of urban and suburban

locations where its rivals Target, Costco, and

K-Mart are less concentrated.

Ü Cross-docking: To eliminate extra storage costs

and maximise efficiency, Wal-Mart’s distribution

centres use cross-docking. Once goods enter

Wal-Mart’s distribution centres, they are crossed

from one loading dock (inbound) to another

(outbound) in 24 hours. This eliminates storage

costs, allows drivers to continuously replenish

Page 26: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

27GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 26

stock at the retail stores, and helps bring unsold

merchandise back to the distribution centre

Costco Wholesale Corporation Ü Founded by James Sinegal in 1976

Ü Largest American ‘membership-only’ warehouse

club

Ü Second largest retailer in the world after Wal-

Mart

Ü As of February 2017, Costco had 727 warehouses

across nine countries. Its in-house label is called

Kirkland Signature

What differentiates Costco?

Costco relies on the following formula: (1) selling a

limited number of items, (2) keeping costs down, (3)

focusing on high volume, (4) paying workers well, (5)

having customers buy memberships, and (6) aiming

for upscale shoppers, especially small-business

owners. In addition to this, it does not advertise,

which results in cost savings of up to 2% of sales per

year.

Ü Low price-high volume: Goods at Costco are

usually bulk-packaged and marketed primarily

to large families and businesses. Costco keeps

product prices low and never marks up any

product more than 15% (less than the typical

25% at super-markets). It earns lesser margins

compared to others, but those low margins

are compensated by charging a US$ 55 annual

membership fee to its 64mn members.

Ü Fewer SKUs and products: Selling fewer items

increase sale volumes and help drive discounts.

Costco warehouse typically carries 3,700

products while a typical Wal-Mart super-centre

carries approximately 140,000 products. Despite

Costco’s large store volume, it sells only four

toothpaste brands while Wal-Mart sells about 60.

Inside of a Costco store

Page 27: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

27GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 26

Ü Only members, warehouse shopping,

no advertising: Costco’s high sales are

achieved without any advertising (no

newspapers, radio, TV, or billboards),

except target-marketing when it opens

a new warehouse. New members

are added due to positive word-of-

mouth from existing members. 91%

of all members currently renew their

membership in US/Canada (i.e.,

attrition rate is only 9%).

Ü Lower operational costs: Costco

drops its shipping pallets directly on

the warehouse floor, no stocking up

products on shelves. This saves millions

in labour cost. Its floors are bare

concrete slabs, which are more durable

and easier to maintain

Aldi Ü Aldi is a common brand of two leading

global discount supermarket chains

– Aldi Nord and Aldi Sud – based in

Germany, with over 10,000 stores in 18

countries

Ü The chain was founded by brothers Karl and

Theo Albrecht in 1946

Ü The two brands operate independently –

internationally, Aldi Nord operates in Denmark,

France, the Benelux countries, the Iberian

Peninsula, and Poland. Aldi Süd operates in

Ireland, United Kingdom, Hungary, Switzerland,

Australia, Austria, and Slovenia.

What differentiates Aldi?

Ü Fewer products: Aldi stacks 1,400 high-volume

products compared to +40,000 products by

supermarkets giants. This leads to less money

tied up in stock. Selling fewer items increases

sales volumes and helps drives discounts. It also

helps Aldi to avoid issues with overstocking and

floor space, which tend to impact the bottomline.

Ü Lower labour cost: Customers at Aldi have

to “rent” a cart by depositing a quarter. The

company says on its website – “By not having

to hire someone to police the shopping carts,

we are able to pass the savings on to our

customers”. Aldi uses boxes instead of shelves

when possible, which frees up workers from

having to stock shelves constantly. Once a

product runs out, the workers simply replace it

with a box.

Ü Efficient workers: At Aldi, only 3-4 employees

are required per shift. They are efficient in

stocking, cleaning, and checking out. They are

compensated well, but keep overall costs down.

Ü Private label: About 90% of the products

at Aldi’s are private label. By eliminating the

middle-man, Aldi can pass on the savings to

customers.

Ü High discounts with consistent quality: The

quality of their private labels might be 10% lower

than classic brands, but they cost 30% lower than

those brands. This means that customers get

more value per money spent.

Weekly ad of Aldi

Page 28: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

29GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 28

ONLINE GROCERY IN INDIA

Tiny, but rising fast

The ecommerce sector in India is expected to have touched about US$ 22bn

in 2015 as per IBEF. E-tailing, which comprises of online retail and online

marketplaces, has become the fastest-growing segment in the larger market

with a 56% CAGR over 2009-14. PWC pegged the size of the e-tail market at

US$ 6bn in 2015. While grocery retailing accounts for almost two-third of the

total retail market in India, online grocery accounts for less than 10% of the

total e-tailing market. Compared to China, Japan, and South Korea, the online

grocery market in India is disproportionately small.

Compared to China, Japan, and South Korea, online grocery market in India is disproportionately small

Online grocery market sizes in 2016 Online grocery growth projections for different countries

Source: Euromonitor 2016 Source: Euromonitor 2016

Page 29: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

29GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 28

History of ecommerce in grocery in IndiaIn India, the first e-commerce start-ups in grocery emerged in 2011-12 with the arrival of Zopnow, BigBasket,

and LocalBanya. Since then, a multitude of online grocery start-ups have mushroomed across India in the last five

years. According to Tracxn, there are at least 490 grocery delivery start-ups in India that have together raised at

least US$ 486mn from investors. However, cracking the online grocery model is not easy. Out of the five largest

online grocery start-ups in India, two have already gone bust.

Headquarters Model Founded Current Status Funding raised

Local Banya Mumbai Mix of hyper-local and market place

May-12 Shut down in October 2015; operated in 4 metros

Undisclosed

Pepper Tap Gurgaon Pure hyper-local model (100%) Sep-14 Shut down in April 2016; operated in 17 cities

US$ 51mn from Sequoia Capital, Snapdeal, SAIF Partners, and others

Big Basket Bangalore Inventory model Dec-11 Operational in 29 cities US$ 220mn in multiple rounds from various investors including Bessemer Venture Partners, International Finance Corp, Abraaj Group

Grofers Gurgaon Hyper-local model , but also uses inventory model for fruits and vegetables

Dec-13 Operational in 17 cities currently.In Jan 2016, it shut opera-tions in 9 cities out of 26.

US$ 165mn fromSoftBank Group Corp., Tiger Global Management Llc, and Sequoia Capital

ZopNow Bangalore Hyper-local model (tie-ups with only a few big retailers)Tied up with HyperCity, More, Star Bazaar and Metro

Sep-11 Operational in 5 metros (11 cities)

Looking to raise US$ 20-30mn

Key Indian online grocery companies

What constitutes a successful model for online grocery?

Like the traditional ecommerce space, there are two business

models in grocery ecommerce – hyper-local model and

inventory. Players using the inventory model (like BigBasket)

use low-cost warehouses on the outskirts of cities and deliver

products directly to customers. Hyper-local delivery players

(like Grofers) procure goods from the local kirana stores and

then deliver the goods to customers. While both models

have their own benefits and drawbacks, most players use a

combination of the two in different proportions.

Zip.in is a Hyderabad-based online grocer that follows the

inventory model. In a guest post on website iamwire.com,

Zip.in’s CEO, Mr Kishore Ganji, highlighted that the hyper-

local delivery model is less promising because of its many

inherent drawbacks, which continue to remain unresolved.

In the post, he wrote that this model suffers from higher

transportation and logistics costs, lower margins, lower ticket

size, and lower control on quality. The result is that hyper-

local start-ups operate on wafer-thin margins and end up

losing money on every delivery. Comparatively, inventory-

based models, in spite of their higher fixed costs, are more

promising as they offer higher margins due to economies of

scale and higher quality control, he had said.

Some players like ZopNow claim to have found a solution

that includes the best of both models. ZopNow is a

Bengaluru-based online grocer that has tied up with big

retailers (such as HyperCity, More, Star Bazaar, and Metro)

for procurement, instead of with multiple local kirana stores.

In media reports, this company has said it believes that

its unique model, which it calls ‘scale-local’, trumps both

warehousing (inventory) and hyper-local models as scale-

local model offers benefits of both without the drawbacks of

either. In a recent interview to vccircle.com, Zop’s CEO, Raj

Pandey had said, “We have opted for the ‘scale-local’ model,

which gives us access to a wide range and optimises logistics

costs as well. While we are not running a warehouse, we have

scale and better unit economics. Plus, there is no pilferage,

no rent, and no utilities.”

Sour

ce: P

hilli

pCap

ital I

ndia

Est

imat

es

Page 30: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

31GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 30

Hyper-local model Inventory model

Format Procure goods from local kirana stores or other retailers as per orders

Own inventory in warehouses

Benefits Asset-lean modelLower fixed costs, lower working capital requirements, and lower pilferage

Enables bulk purchases, which brings down procurement costsProvides economies of scaleFacilitates large order deliveries

Drawbacks High transportation and logistics costsQuality of products cannot be controlledLimited choice and limited quantity of products

Higher fixed costsHigher working capital requirement

Characteristics of online grocery models

So what is the right strategy for online

grocery in India?

The key differentiating factors between traditional

ecommerce and grocery ecommerce are – delivery

times (faster delivery expected for grocery due

to perishability of goods), gross margins, ticket

size, and nature of products (includes perishable

goods). Gross margins are lower in groceries (vs.

say white goods), but swift deliveries, in fact, cost

more – hence grocery companies need an adequate

ticket size to generate sufficient gross profits and

make each delivery profitable. Currently, even

existing online grocery customers order only a

portion of their groceries online, and purchase the

rest from nearby kirana outlets or modern retail

stores. To increase ticket size, companies will have

to continually provide highest levels of service and

ensure more business from each customer per order.

Lack of well-developed cold-storage infrastructure

in India is one of the major challenges for Indian

online grocers. Unlike traditional e-commerce

players, online grocers need strong cold-storage

infrastructure for storing and transportation of

perishable goods. As a result, online grocery

companies which will invest in cold-storage

infrastructures in their target markets will be able

to deliver high-quality products to their consumers.

This will help ensure repeat orders and also help to

increase ticket sizes.

Like many traditional organised retailers who went

bust while trying to expand too quickly, many

major online grocery players have also gone bust

for the same reason. This is because setting up the

sourcing, warehousing and distribution of groceries

for online sales requires building of infrastructure

at the local level. Rapid expansion across the entire

country without focus on supply chains will lead to a

significant increase in procurement and distribution

costs, and make businesses unsustainable. Grofers

learnt it the hard way in January 2016 when it

had to shut operations in 9 out of 26 cities due to

sustainability issues after rapid expansion.

Building a localised supply chain is essential for a business like online grocery

While the debate about which model is superior rages on, the success of both Grofers (hyper-local) and BigBasket (inventory) indicates that both models can work with the right strategy

Page 31: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

31GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 30

Will India go the US way or the China way?

The Indian market has high population density and is heavily fragmented (like China) but does not have a developed transport and cold storage infrastructure (unlike China)

Since both online grocery and modern retail offer unique benefits to customers compared to unorganised retailers, and target different sets of customers, in India, both these formats will grow faster than the overall grocery retail market

Modern retail and online grocery will both grow

faster than the overall grocery market

Online grocery and modern retail have both grown faster

than the respective retail markets in China and other

countries, by gaining market share from unorganised

retailers. Both online grocery and modern retail offer

customers a one-stop solution and variety, which is not

available in unorganised retail outlets. Also, unorganised

retail does not offer huge savings offered by modern retail or

home delivery offered by online grocery. Since both online

grocery and modern retail offer unique benefits to customers

compared to unorganised retailers and target different sets

of customers, even in India, both modern retail and online

grocery will grow faster than the overall grocery market.

Share of modern retail in China continued to grow

even as online grocery expanded over 2012-15 – both

these segments gained market share from traditional

retail channels.

Share of various formats in Chinese retail industry

Each market is different

While China and many developed nations have seen a sharp

growth in online grocery over the last decade, the US online

grocery market stands out as being disproportionately

smaller. This could be due to the following reasons: (1)

Population density and concentration in the US is lower

than in China and other developed nations, which makes

grocery ecommerce less feasible due to high delivery and

warehousing costs, and (2) the dominance of Walmart and

Kroger (42% combined share) over the US grocery markets

has reduced the innovation intensity in the industry.

The Indian market seems to have more in common to

China than the US – high population density and heavily

fragmented retail markets. However, unlike China, the cold

storage infrastructure is still in nascent stages in India and

there are many other supply-chain bottlenecks in the country,

which will only ease with time. As a result, the growth in

online grocery market in India is likely to be more gradual

than that in China.

Source: Kantar world panel report

Sour

ce: N

eilse

n, E

&Y

Page 32: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

33GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 32

BY SURYA NARAYAN PATRA

GV spoke to Ms Anu Acharya, the CEO of Mapmygenome, an Indian genomics company whose vision is better health for India using technology. This company provides a range of prognostics, diagnostics, and brain-wellness solutions. With several awards to her name, Ms Acharya has rich experience in telecom, IT, and entrepreneurship. She has studied at IIT (Kharagpur) and University of Illinois, from where she has two post-graduate degrees (Physics, MIS). She is a member of the World Economic Forum’s ‘Personalized and Precision Medicine Council’.

Precision medicines is the future for

Molecular DiagnosticsCould you briefly outline Mapmygenome’s

business model and service offerings?

Mapmygenome is a genomics company that

offers personalised health solutions based on

genetic tests. By combining the genetic health

profile and health history with genetic counselling,

Mapmygenome provides actionable steps for

individuals and their physicians towards a healthier

life. Mapmygenome is focused on predictive tests,

apart from other diagnostics tests.

Under predictive tests, it has a flagship product

‘Genomepatri’. It is a once-in-a-lifetime, non-

invasive personal genomics test that gives a

comprehensive health profile – for better health

management. With a simple saliva swab sent from

the convenience of a person’s home, a customer

can learn about genetic predispositions to 120+

conditions – physical attributes, lifestyle, disease

risks, inherited conditions, and response to

medications.

Page 33: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

33GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 32

Unlike the traditional annual physical exam that

detects manifested conditions, we assess disease

risks and offer mitigation assistance through a

genetic-counselling session. Our counsellors

correlate test results with family history and current

lifestyle to offer actionable steps to better health.

In addition to Genomepatri, we have a range of

products and services spanning personal genomics,

molecular diagnostics, brain wellness, and TB

diagnostic kits. In diagnostic services, we offer full

genome sequencing, Whole Exome Sequencing,

and different panel tests.

How is your business different from the molecular

tests offered by other diagnostic chains?

Other diagnostic chains do not have the range

of molecular tests that MapMyGenome provides.

Even if the chains are selling complex tests, they

would be outsourced (either to MapMyGenome

or others). The common molecular test offerings

are similar across all diagnostic service providers,

but predicative test offerings are what differentiate

our company. In fact, our intellectual property

(IP) in the predicative test space and over 22,000

gene-expression sample data from genome

sequencing tests are our biggest advantage. We see

interpretation of genome sequencing data as more

important, so our vast database on gene expression

gives us an edge over other players, as diagnostic

chains may not have such as vast data library.

MapMygeneome also provides genetic counselling

along with test offerings.

While the Indian diagnostics market is estimated

at about US$ 6bn, molecular tests’ market share

is believed to be marginal. How big is this market

in India?

The growth of the molecular test market has been

much faster than overall diagnostics – at 28-29% –

over the last few years, but the size is relatively small.

We estimate the molecular market size at about

~US$ 220mn.

Molecular test offerings in India are largely

city-centric due to limited awareness and low

affordability. How do you see this industry

evolving in India and what are key future growth

drivers? What are the key challenges?

We see rapid progress in the Indian genetic tests

market and believe that it will see accelerated growth

in coming years. MapMyGenome itself has tripled its

business over the last four years. However, we believe

the molecular market can reach the next level only

led by government facilitation in building advanced

infrastructure (which is really expensive and is the

key challenge for this sector) and wider insurance

coverage. In countries such as China, US, and the

UK, we have seen the government becoming actively

involved in much-needed research and infrastructure

creation – but this approach is lacking in India. Unless

we see any progress here, the genetic tests market

will remain less penetrated and expensive.

What is the prevailing competitive landscape in the

Indian molecular tests market and who are your

key peers?

Although there are multiple diagnostic chains who

offer few common genetic tests, competition in

complex genetic tests is limited to a few players

– MapMyGenome, Make Genome, and Strand

Life Science. Mostly, diagnostic chains outsource

complex genetic tests to players like us. For example,

diagnostic players and chains including Metropolis, Dr

Lal Path Labs, Cryoviva, Cryosafe, Onquest, 1mg, and

Lucid Diagnostics outsource the advanced genetic

tests to MapMyGenome.

Volume seems to be a key success factor in

diagnostics, but that is very low for molecular

tests. Do you think doctors play a critical role in

the success of any molecular diagnostic business?

Hospitals and doctors are certainly the prime source

for volume for our genetic test offerings, but we

have more direct walk-in patients. Our focus on

the predictive genetic tests drives these walk-ins.

Additionally, rising awareness and attitude towards

health will gradually drive volume growth.

Page 34: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

35GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 34

What price trend do you foresee in the molecular

diagnostics business and what would drive that?

The price point has already seen a sharp erosion, led

by technology advancement over the last 10 years.

Genomic tests that used to cost US$ 200mn 10 years

ago are now available at US$ 1500-2000. I believe

prices can fall further supported by technology

and rising awareness about molecular diagnostics.

MapMyGenome started offering genome tests at

a price of Rs 25,000, which we have now cut to Rs

15,000 over the last couple of years. Technology-

led price disruption is a possible trend in molecular

diagnostics.

In pathological diagnostics, equipment, reagents,

and infrastructure are key cost elements and

determine the pricing. This is also the case in

molecular diagnostics. So rising volumes would

certainly help with falling prices.

Do you believe the concept of ‘precision

medicines’? Is this the future for molecular

diagnostics?

The concept of precision medicine emerged from

the fact that one drug does not suit everybody due

to the difference in patients’ genetic makeups. This

relatively new field combines pharmacology (the

science of drugs) and genomics (the study of genes

and their functions) to develop effective and safe

medications as per the patients’ genetic makeup.

Inappropriate use of medicines is not only

widespread, but it is also costly and extremely

harmful – both to individuals and the general

population. As per industry surveys, adverse drug

events rank among the top-10 causes of death in the

USA and are estimated to cost between US$ 30bn

and US$ 130bn each year.

Precision medicine is certainly the future of

molecular tests and its application is not restricted

to only advanced markets. MapMyGenome plays

an important role in India in the space of precision

medicines under its service offering – MedicaMap,

which covers almost 100 different drug compounds

spanning 35 pharmacological classes. The test offers

comprehensive screening for medicines in major

specialties like cardiology, oncology, immunology,

psychiatry, infectious diseases, diabetology,

neurology, gastroenterology, endocrinology, and

toxicology.

Is there any international business potential? Do

you find business scope in outsourced biologics

services?

Our company is already into exports with a presence

in more than 42 countries, but we do not have a

presence in advanced markets such as the US or UK.

There is vast export opportunity for Indian players.

Medical tourism will create a good opportunity for

molecular tests.

The rising global outlook in biologics services

could certainly prove key growth drivers for Indian

molecular diagnostic, internationally. There are many

players who already provide biological services at

the global level, and genetic test providers have

enough capability to complement Indian biological

service providers in the international market.

DNA sequence variations in the human genome alter biological factors such as protein function. Most of these proteins are key catalysts for the metabolism of drug compounds, which translates into inter-individual variability in drug response. The pharmacogenomics that studies an individual’s response to drugs for therapeutic benefit and design the medication is called precision medicines

Page 35: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

35GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 34

Indian Economy – Trend Indicators

Monthly Economic Indicators

Quarterly Economic Indicators

Growth Rates (%) Feb-16 Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16 Oct-16 Nov-16 Dec-16 Jan-17 Feb-17 Mar-17

IIP 2.0 0.3 -1.3 1.1 2.0 -2.5 -0.7 0.7 -1.8 5.7 -0.1 2.7 -1.2

PMI 51.1 52.4 50.5 50.7 51.7 51.8 52.6 52.1 54.4 52.3 49.6 50.4 50.7 52.5

Core sector 5.7 6.4 8.5 2.8 5.2 3.0 3.2 5.0 6.6 4.9 5.6 3.4 1.0

WPI -1.0 -0.9 0.3 0.8 1.6 3.5 3.9 3.8 3.8 3.2 3.4 5.2 6.5 5.7

CPI 4.4 4.8 5.5 5.8 5.8 6.1 5.0 4.4 4.2 3.6 3.4 3.2 3.7 3.8

Money Supply 11.3 10.3 10.0 10.1 10.4 10.4 10.3 12.1 10.9 8.5 6.2 6.4 6.5 7.3

Deposit 11.0 9.9 9.3 9.5 9.7 9.5 9.2 11.3 9.8 15.3 14.5 13.2 12.1 11.2

Credit 11.6 11.3 9.2 9.8 9.4 9.7 9.6 11.2 8.5 4.7 4.7 4.62 4.4 4.7

Exports -5.7 -5.5 -6.7 -0.8 1.3 -6.8 -0.3 4.6 9.6 2.3 5.7 4.3 17.5 27.6Imports -5.0 -21.6 -23.1 -13.2 -7.3 -19.0 -14.1 -2.5 8.1 10.4 0.5 10.7 21.8 45.3Trade deficit (USD Bn) -6.5 -5.1 -4.8 -6.3 -8.1 -7.8 -7.7 -8.3 -10.2 -13.0 -10.4 -9.8 -8.9 -10.4Net FDI (USD Bn) 2.8 1.4 2.0 1.5 3.3 3.6 4.4 4.6 2.4 2 3 3 0.9

FII (USD Bn) -2.4 4.3 1.1 -0.4 -0.2 2.7 1.0 3.0 -1.8 -3.8 -4.0 -0.4 2.5

ECB (USD Bn) 1.4 1.5 0.3 1.3 1.1 1.2 3.2 1.6 1.5 0.3 2.5 1.8 2.2

Dollar-Rupee 68.4 66.2 66.3 67.3 67.5 67.0 67.0 66.6 66.8 68.4 67.9 67.9 66.7 64.9

FOREX Reserves (USD Bn) 346.8 355.6 361.6 360.2 360.8 365.5 366.8 372.0 367.2 365.3 360.3 361.6 362.8 370.0

Balance of Payment (USD Bn) Q2FY15 Q3FY15 Q4FY15 Q1FY16 Q2FY16 Q3FY16 Q4FY16 Q1FY17 Q2FY17Exports 85.3 79.0 70.8 68.0 67.6 64.9 65.8 66.6 67.4Imports 123.9 118.3 102.5 102.2 104.7 98.9 90.6 90.4 93.1Trade deficit -38.6 -39.3 -31.7 -34.2 -37.2 -34.0 -24.8 -23.8 -25.6Net Invisibles 28.5 30.9 30.2 28.0 28.6 26.9 24.4 23.5 22.2CAD -10.1 -8.4 -1.5 -6.1 -8.6 -7.1 -0.3 -0.3 -3.4CAD (% of GDP) 2.0 1.7 0.3 1.2 1.7 1.3 0.1 0.0 0.0Capital Account 16.5 23.6 30.7 18.6 8.1 10.9 3.5 7.1 12.7BoP 6.9 13.2 30.1 11.4 -0.9 4.1 3.3 7.0 8.5

GDP and its Components (YoY, %) Q4FY15 Q1FY16 Q2FY16 Q3FY16 Q4FY16 Q1FY17 Q2FY17 Q3FY17

Agriculture & allied activities -1.7 2.5 2.0 -1.0 2.3 1.8 3.8 6.0Industry 6.9 7.1 8.5 10.3 9.2 7.7 8.5 10.8Mining & Quarrying 10.1 8.5 5.0 7.1 8.6 -0.4 -1.3 7.5Manufacturing 6.6 7.3 9.2 11.5 9.3 9.1 6.9 8.3Electricity, Gas & Water Supply 4.4 4.0 7.5 5.6 9.3 9.4 3.8 6.8Services 8.3 8.3 7.9 8.5 8.1 8.4 7.5 5.0Construction 2.6 5.6 0.8 4.6 4.5 1.5 3.4 2.7Trade, Hotel, Transport and Communications 13.1 10.0 6.7 9.2 9.9 8.1 6.9 7.2Finance, Insurance, Real Estate & Business Services 9.0 9.3 11.9 10.5 9.1 9.4 7.6 3.1Community, Social & Personal Services 4.1 5.9 6.9 7.2 6.4 12.3 11.0 11.9GDP at FC 6.2 7.2 7.3 6.9 7.4 7.3 6.7 6.6

Page 36: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

37GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 36

Annual Economic Indicators and Forecasts Indicators Units FY9 FY10 FY11 FY12 FY13 FY14 FY15 FY16E FY17E FY18E

Real GDP/GVA growth % 6.7 8.6 8.9 6.7 4.9 5.6 7.1 7.2 6.8 7.4

Agriculture % 0.1 0.8 8.6 5 1.2 4.3 -0.2 1.2 4 3

Industry % 4.1 10.2 8.3 6.7 5.1 0.4 6.5 8.8 5.5 10.6

Services % 9.4 10 9.2 7.1 6 8.2 9.4 8.2 7.8 7.4

Real GDP Rs Bn 41587 45161 49185 52475 54821 90844 97275 104272 111362 119603

Real GDP US$ Bn 908 953 1079 1096 1008 1503 1595 1604 1662 1772

Nominal GDP Rs Bn 56301 64778 77841 90097 101133 112728 124882 135762 150594 168176

Nominal GDP US$ Bn 1229 1367 1707 1881 1859 1864 2047 2089 2248 2491

WPI (Average) % 8.1 3.8 9.6 8.7 7.4 6 2 -2.5 3 3

CPI (Average) 9 12.4 10.4 8.3 10.2 9.5 6.4 4.9 4.6 4

Money Supply % 20.5 19.2 16.2 15.8 13.6 13.5 12 10.3 11 11.5

CRR % 5 5.75 6 4.75 4 4 4 4 4 4

Repo rate % 5 5 6.75 8.5 7.5 8 7.5 6.75 5.75 5.25-5.5

Reverse repo rate % 3.5 3.5 5.75 7.5 6.5 7 6.5 5.75 5.25 4.75-5

Bank Deposit growth % 19.9 17.2 15.9 13.5 14.2 14.6 12.1 9.7 14 8

Bank Credit growth % 17.5 16.9 21.5 17 14.1 13.5 12.5 10.7 8 9

Centre Fiscal Deficit Rs Bn 3370 4140 3736 5160 5209 5245 5107 5351 5339 5045

Centre Fiscal Deficit % of GDP 6 6.4 4.8 5.7 5.2 4.6 4.1 3.9 3.5 3

State Fiscal Deficit % of GDP 2.4 2.9 2.1 1.9 2 2.2 2.9 2.4 2.7 2.8

Consolidted Fiscal Deficit % of GDP 8.4 9.3 6.9 7.6 6.9 7.1 6.6 6.3 6.2 5.8-6

Exports US$ Bn 189 182.4 251.1 309.8 306.6 318.6 316.7 266.4 275.7 279.8

YoY Growth % 13.7 -3.5 37.6 23.4 -1 3.9 -0.6 -15.9 3.5 1.5

Imports US$ Bn 308.5 300.6 381.1 499.5 502.2 466.2 460.9 396.4 392.5 412.1

YoY Growth % 19.7 -2.5 26.7 31.1 0.5 -7.2 -1.1 -14 -1 5

Trade Balance US$ Bn -119.5 -118.2 -129.9 -189.8 -195.6 -147.6 -144.2 -130.1 -116.8 -132.3

Net Invisibles US$ Bn 91.6 80 84.6 111.6 107.5 115.2 116.2 107.9 102.9 106.5

Current Account Deficit US$ Bn -27.9 -38.2 -45.3 -78.2 -88.2 -32.4 -27.9 -22.2 -13.9 -25.8

CAD (% of GDP) % -2.3 -2.8 -2.6 -4.2 -4.7 -1.7 -1.4 -1.1 -0.6 -1

Capital Account Balance US$ Bn 7.8 51.6 62 67.8 89.3 48.8 90 41.1 39 63.4

Dollar-Rupee (Average) 45.8 47.4 45.6 47.9 54.4 60.5 61.2 65.5 67 67.5

Source: RBI, CSO, CGA, Ministry of Agriculture, Ministry of commerce, Bloomberg, PhillipCapital India Research

Page 37: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

37GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 36

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

Mah

indr

a CIE

Auto

mob

iles

229

8

6,58

8 5

4,17

0 6

6,95

6 6

,497

9

,384

3

,147

5

,040

1

0 1

3 9

0.4

37.

1 2

3.5

17.

2 3

.3

2.0

1

3.8

9.0

1

4.0

13.

7 1

2.1

21.

6

Asho

k Ley

land

Auto

mob

iles

82

233

,789

2

01,6

21

238

,868

2

2,79

4 2

6,38

9 1

2,35

1 1

5,06

3 4

5

1

1.2

22.

0 1

8.9

15.

5 3

.6

3.0

1

0.0

8.2

1

8.8

19.

0 1

5.7

17.

0

Ceat

Ltd

Auto

mob

iles

1,4

72

59,

543

57,

810

69,

397

6,8

15

8,6

23

3,6

18

4,8

02

89

118

-2

1.0

32.

7 1

6.6

12.

5 2

.5

2.2

9

.2

7.2

1

5.3

17.

3 1

5.2

17.

2

Apol

lo Ty

res

Auto

mob

iles

239

1

21,8

61

133

,058

1

49,7

45

19,

925

21,

437

10,

308

11,

156

20

22

-1.4

8

.2

11.

8 1

0.9

1.7

1

.5

7.0

6

.5

14.

5 1

3.7

10.

9 1

0.5

Esco

rts Lt

dAu

tom

obile

s 5

50

67,

399

41,

021

46,

888

3,2

09

4,6

39

2,1

62

3,1

81

18

27

108

.1

47.

1 3

0.3

20.

6 3

.2

2.8

2

0.7

13.

8 1

0.5

13.

5 9

.0

12.

4

Baja

j Aut

oAu

tom

obile

s 2

,828

8

18,2

00

220

,067

2

56,2

25

47,

024

54,

642

39,

729

46,

098

137

1

59

8.8

1

6.0

20.

6 1

7.8

5.6

4

.7

16.

9 1

4.3

27.

3 2

6.5

28.

1 2

7.6

Hero

Mot

oCor

pAu

tom

obile

s 3

,214

6

41,8

96

281

,283

3

21,4

96

48,

228

53,

656

34,

710

38,

689

174

1

94

10.

8 1

1.5

18.

5 1

6.6

6.7

5

.6

13.

3 1

1.9

36.

5 3

3.7

35.

2 3

3.2

Tata

Mot

ors

Auto

mob

iles

447

1

,428

,430

2

,678

,907

3

,078

,324

3

31,7

59

434

,799

8

0,11

2 1

36,2

32

25

42

-27.

5 7

0.1

17.

9 1

0.6

1.6

1

.4

5.5

4

.2

9.2

1

3.7

4.7

7

.3

Mar

uti S

uzuk

iAu

tom

obile

s 6

,285

1

,898

,498

6

65,3

40

753

,298

1

06,1

88

118

,994

7

3,46

9 8

2,49

6 2

43

273

6

0.7

12.

3 2

5.8

23.

0 5

.8

4.8

1

7.7

15.

7 2

2.3

20.

8 2

2.6

21.

2

Mah

indr

a & M

ahin

dra

Auto

mob

iles

1,2

72

789

,843

4

08,7

12

454

,622

5

4,76

7 6

1,82

9 3

4,26

0 3

9,16

9 5

8 6

6 4

.1

14.

3 2

2.0

19.

2 3

.0

2.7

1

4.5

12.

7 1

3.8

14.

2 1

1.9

12.

6

Bhar

at Fo

rge

Auto

mob

iles

1,0

88

253

,175

7

1,42

5 8

1,20

4 1

3,46

4 1

6,44

3 6

,084

8

,369

2

6 3

6 -7

.1

37.

6 4

1.6

30.

3 6

.4

5.6

1

9.9

16.

2 1

5.4

18.

5 1

1.8

14.

8

Siem

ens

Capi

tal G

oods

1,3

17

468

,993

1

08,0

89

115

,924

9

,731

1

3,30

5 6

,056

8

,518

1

7 2

4 4

.6

40.

6 7

7.4

55.

1 7

.1

6.7

4

4.6

32.

2 9

.2

12.

2 3

8.2

9.8

ABB

Indi

aCa

pita

l Goo

ds 1

,417

3

00,1

89

86,

484

103

,243

7

,547

1

0,34

2 3

,612

5

,445

1

7 2

6 1

1.6

50.

7 8

3.1

55.

1 9

.1

8.3

3

9.0

28.

7 1

1.0

15.

1 9

.6

13.

1

Ther

max

Capi

tal G

oods

1,0

08

120

,110

4

5,60

3 5

0,49

5 4

,014

4

,655

2

,996

3

,257

2

5 2

7 8

.8

8.7

4

0.1

36.

9 4

.7

4.3

2

9.3

24.

7 1

1.6

11.

6 1

0.0

11.

0

Engi

neer

s Ind

iaCa

pita

l Goo

ds 1

70

114

,289

1

3,90

1 1

9,55

3 3

,063

2

,784

3

,350

3

,270

5

5

3

1.8

-2.4

3

4.1

35.

0 4

.2

4.1

2

7.9

30.

9 1

2.2

11.

7 1

3.5

12.

8

Inox

Win

dCa

pita

l Goo

ds 2

06

45,

760

46,

885

51,

662

7,0

25

7,7

65

4,1

91

4,5

78

19

21

-8.0

9

.2

10.

9 1

0.0

2.1

1

.8

7.6

6

.4

19.

3 1

8.2

14.

1 1

3.5

Cum

min

s Ind

iaCa

pita

l Goo

ds 9

47

262

,536

5

1,13

7 5

8,29

6 8

,639

1

0,17

9 7

,897

9

,115

2

8 3

3 4

.7

15.

4 3

3.2

28.

8 6

.9

6.3

3

0.5

25.

7 2

0.8

22.

0 2

0.2

21.

3

KEC

Inte

rnat

iona

lCa

pita

l Goo

ds 2

23

57,

318

84,

462

91,

484

7,6

07

8,2

47

2,5

80

3,1

02

10

12

14.

3 2

0.2

22.

2 1

8.5

3.3

2

.9

10.

1 9

.2

15.

0 1

5.7

9.9

1

0.6

Lars

en &

Toub

roCa

pita

l Goo

ds 1

,685

1

,572

,095

1

,110

,087

1

,274

,713

1

20,9

94

144

,127

5

7,87

4 6

7,26

2 6

2 7

2 3

8.2

16.

2 2

7.1

23.

3 3

.2

3.0

1

9.9

16.

8 1

2.0

12.

6 5

.0

5.6

VA Te

ch W

abag

Capi

tal G

oods

693

3

7,81

9 3

0,14

7 3

7,43

5 2

,858

3

,557

1

,348

1

,752

2

5 3

2 5

1.6

30.

0 2

8.1

21.

6 3

.6

3.2

1

3.5

11.

0 1

2.7

14.

8 9

.9

11.

4

Volta

sCa

pita

l Goo

ds 4

22

139

,518

5

9,99

8 7

1,71

0 5

,626

7

,056

4

,654

5

,383

1

4 1

6 4

7.0

15.

7 3

0.0

25.

9 4

.3

3.8

2

4.5

19.

4 1

4.3

14.

6 1

6.5

15.

4

BHEL

Capi

tal G

oods

176

4

30,6

55

299

,845

3

45,4

30

12,

599

29,

244

9,4

66

20,

956

4

9

-204

.3

121

.4

45.

5 2

0.6

1.3

1

.2

26.

3 1

1.5

2.8

5

.9

2.1

4

.4

JK La

kshm

i Cem

ent

Cem

ent

469

5

5,18

7 3

7,76

3 4

5,17

5 6

,005

8

,230

1

,503

2

,999

2

1 4

3 1

37.1

9

9.5

21.

8 1

0.9

1.9

1

.8

13.

6 9

.8

8.9

1

6.3

6.4

9

.1

JK C

emen

tCe

men

t 9

39

65,

666

37,

763

45,

175

6,0

05

8,2

30

1,5

03

2,9

99

21

43

137

.1

99.

5 4

3.7

21.

9 3

.9

3.6

1

5.3

11.

0 8

.9

16.

3 6

.4

9.1

Dalm

ia B

hara

t Ltd

Cem

ent

2,1

20

188

,576

8

1,11

4 8

6,85

8 2

0,30

4 2

3,39

7 5

,248

5

,845

5

9 6

6 1

74.8

1

1.4

35.

9 3

2.2

4.3

3

.8

12.

0 1

0.0

12.

0 1

1.9

8.4

8

.6

Page 38: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

39GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 38

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

Heid

elbe

rgCe

men

t Ce

men

t 1

33

30,

242

18,

244

19,

946

2,4

54

3,1

82

676

1

,164

3

5

7

4.9

72.

2 4

4.7

26.

0 3

.2

2.8

1

5.1

10.

9 7

.1

10.

9 6

.6

8.6

OCL I

ndia

Cem

ent

1,0

00

56,

900

29,

529

33,

165

5,8

57

6,5

92

3,2

24

3,7

21

57

65

57.

5 1

5.4

17.

7 1

5.3

3.5

2

.9

9.2

7

.7

19.

5 1

9.3

17.

5 2

0.6

Indi

a Cem

ent

Cem

ent

188

5

7,67

3 6

0,03

5 6

6,59

2 1

0,22

6 1

1,47

2 2

,601

3

,949

8

1

3 8

0.1

50.

9 2

2.2

14.

7 1

.6

1.5

7

.9

6.6

7

.3

10.

4 7

.5

9.3

Ultra

tech

Cem

ent

Cem

ent

4,0

14

1,1

01,9

16

279

,403

3

52,8

15

54,

309

69,

379

28,

669

29,

712

104

1

08

25.

4 3

.6

38.

4 3

7.1

4.7

4

.2

20.

7 1

9.0

12.

2 1

1.4

9.8

8

.6

Man

gala

m C

emen

tCe

men

t 3

85

10,

277

8,8

01

9,8

35

1,1

68

1,5

55

280

6

17

11

23

-237

.0

119

.8

36.

6 1

6.7

2.0

1

.8

13.

1 9

.4

5.4

1

0.9

5.3

8

.1

Ambu

ja C

emen

tCe

men

t 2

42

480

,427

9

8,75

4 1

08,6

82

17,

340

21,

077

10,

163

12,

052

6

6

10.

3 5

.6

42.

1 3

9.9

5.4

5

.7

26.

9 2

2.0

12.

8 1

4.3

9.9

1

2.7

ACC

Cem

ent

1,5

07

282

,958

1

09,4

56

129

,581

1

1,98

8 1

4,97

7 6

,430

7

,696

3

4 4

1 -1

4.5

19.

7 4

4.1

36.

8 3

.3

3.2

2

2.0

17.

8 7

.4

8.6

7

.0

7.5

Shre

e Ce

men

tCe

men

t17

586

612

,656

9

0,77

2 9

8,58

4 3

1,83

3 3

5,74

8 1

8,38

1 2

0,31

1 5

28

583

2

03.1

1

0.5

33.

3 3

0.2

8.0

6

.6

18.

7 1

6.2

24.

0 2

1.9

23.

2 2

3.1

KEI I

ndus

tries

ELEC

TRIC

ALS

212

1

6,48

5 2

6,32

8 2

9,98

3 2

,797

3

,231

2

,522

2

,940

3

3 3

8 1

6.2

16.

6 6

.5

5.6

3

.6

3.0

7

.8

6.6

5

6.0

53.

4 2

6.6

28.

3

Finol

ex C

able

s Ltd

ELEC

TRIC

ALS

543

8

2,98

5 5

,154

6

,278

6

57

861

2

81

400

8

1

2 -1

2.3

42.

6 6

6.3

46.

5 8

.1

7.1

1

28.0

9

7.8

12.

2 1

5.3

12.

9 1

4.3

VGua

rd In

dustr

ies L

tdEL

ECTR

ICAL

S 1

86

78,

773

5,1

54

6,2

78

657

8

61

281

4

00

8

12

-12.

3 4

2.6

22.

7 1

5.9

2.8

2

.4

121

.6

92.

9 1

2.2

15.

3 1

2.9

14.

3

Baja

j Ele

ctrica

ls Lt

dEL

ECTR

ICAL

S 3

55

35,

948

46,

946

50,

568

2,6

05

2,9

89

1,0

69

1,2

84

11

13

11.

8 2

0.0

33.

5 2

7.9

4.3

3

.8

15.

7 1

3.5

12.

7 1

3.5

10.

6 1

1.1

Have

lls In

dia L

tdEL

ECTR

ICAL

S 4

93

308

,179

5

9,50

6 8

5,19

1 8

,118

1

0,61

9 5

,662

6

,558

9

1

0 1

0.4

15.

8 5

4.4

47.

0 1

0.6

9.4

3

8.3

29.

2 1

9.5

20.

1 1

6.1

17.

3

Shrir

am Tr

ansp

ort

Finan

ceFin

ancia

ls 1

,080

2

44,9

65

57,

120

61,

055

44,

322

44,

772

15,

940

17,

479

70

77

35.

3 9

.7

15.

4 1

4.0

0.0

0

.0

5.5

5

.5

14.

7 1

4.2

2.2

2

.0

Chol

aman

dala

m In

ves

Finan

cials

1,0

52

164

,357

2

5,09

5 3

0,64

0 1

5,41

7 1

8,77

8 7

,487

9

,427

4

8 6

0 3

1.7

25.

9 2

1.9

17.

4 0

.0

0.0

1

0.7

8.8

1

8.8

19.

9 2

.5

2.6

Man

appu

ram

Fina

nce

Finan

cials

98

82,

759

18,

570

23,

348

10,

454

13,

306

6,5

39

8,4

15

8

10

93.

9 2

8.7

12.

6 9

.8

2.5

2

.1

7.9

6

.2

21.

9 2

3.4

4.9

5

.1

Mah

indr

a & M

ah Fi

nFin

ancia

ls 3

38

192

,356

3

2,30

2 3

8,17

6 1

8,55

2 2

2,91

2 4

,625

8

,735

8

1

5 -3

1.2

88.

9 4

1.3

21.

9 0

.0

0.0

1

0.4

8.4

7

.5

13.

3 1

.1

1.8

Shrir

am C

ity U

nion

Fin

Finan

cials

2,2

90

151

,033

2

8,47

4 3

3,58

2 1

6,67

5 1

9,75

8 6

,286

7

,725

9

5 1

17

18.

6 2

2.9

24.

0 1

9.5

0.1

0

.1

9.1

7

.6

13.

2 1

4.5

2.8

2

.9

Mut

hoot

Fina

nce

Finan

cials

416

1

66,1

42

29,

972

34,

858

18,

191

21,

430

11,

592

13,

627

29

34

43.

2 1

7.6

14.

3 1

2.2

2.6

2

.2

9.1

7

.8

19.

1 1

9.4

4.0

4

.1

Unio

n Ba

nk

Finan

cials

156

1

07,4

47

134

,300

1

39,7

42

70,

560

70,

010

5,7

27

10,

305

8

12

-60.

4 5

3.8

20.

1 1

3.1

0.5

0

.5

1.5

1

.5

2.7

4

.5

0.1

0

.2

Orie

ntal

Ban

k of C

omFin

ancia

ls 1

55

53,

483

79,

612

79,

078

44,

505

40,

013

2,8

45

4,6

53

8

12

69.

3 4

9.2

18.

8 1

2.6

0.4

0

.4

1.2

1

.3

2.0

3

.1

0.1

0

.2

ICIC

I Ban

kFin

ancia

ls 2

73

1,5

92,0

36

412

,489

3

74,3

67

268

,614

2

10,8

17

85,

083

71,

498

15

12

-12.

7 -1

6.1

18.

7 2

2.3

1.7

1

.6

5.9

7

.6

9.2

7

.4

1.7

1

.6

Repc

o Ho

me

Finan

ce

Finan

cials

772

4

8,29

4 4

,038

5

,068

3

,326

4

,163

1

,802

2

,354

2

9 3

7 2

0.0

29.

8 2

6.8

20.

7 0

.1

0.1

1

4.5

11.

6 1

7.4

19.

2 2

.0

2.1

Stat

e Ba

nk o

f Ind

iaFin

ancia

ls 2

86

2,3

19,4

19

915

,543

9

30,6

47

454

,303

4

23,1

06

102

,503

1

32,5

82

13

16

-0.6

2

7.8

22.

4 1

7.6

1.3

1

.2

5.1

5

.5

6.7

8

.0

0.4

0

.5

Bank

of B

arod

a Fin

ancia

ls 1

80

414

,057

1

93,9

81

201

,585

1

03,5

33

101

,905

1

5,69

3 2

8,91

6 7

1

3 -1

29.1

8

4.3

26.

5 1

4.4

1.1

1

.0

4.0

4

.1

4.3

7

.5

0.2

0

.4

Page 39: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

39GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 38

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

Indi

an B

ank

Finan

cials

260

1

24,7

56

73,

085

79,

100

39,

912

43,

322

14,

413

16,

492

30

34

102

.6

14.

4 8

.7

7.6

0

.8

0.8

3

.1

2.9

1

0.5

10.

5 0

.7

0.7

HDFC

Ban

kFin

ancia

ls 1

,468

3

,761

,817

4

48,7

60

533

,934

2

52,2

00

304

,517

1

46,3

89

176

,839

5

8 7

0 1

9.1

20.

8 2

5.4

21.

0 0

.9

0.8

1

4.9

12.

4 1

8.7

19.

4 2

.0

2.0

Indu

sind

Bank

Finan

cials

1,4

40

861

,375

1

00,1

56

125

,481

5

3,02

0 6

7,91

5 2

9,68

3 3

8,41

3 5

0 6

4 2

9.4

29.

4 2

9.0

22.

4 4

.3

3.7

1

6.2

12.

7 1

5.7

17.

5 2

.0

2.1

HDFC

Lim

ited

Finan

cials

1,5

25

2,4

22,7

16

115

,002

1

26,8

02

106

,625

1

17,3

85

73,

588

81,

113

47

51

3.7

1

0.2

32.

7 2

9.7

0.0

0

.0

22.

7 2

0.6

20.

4 2

0.1

2.5

2

.4

LIC H

ousin

g Fin

ance

Finan

cials

643

3

24,5

49

38,

395

41,

105

32,

208

33,

989

19,

217

20,

805

38

41

15.

7 8

.3

16.

9 1

5.6

0.0

0

.0

9

.5

19.

4 1

8.0

1.4

1

.3

Punj

ab N

atio

nal B

ank

Finan

cials

156

3

32,0

69

248

,616

2

51,6

56

129

,150

1

18,3

86

15,

749

30,

400

7

-135

.8

-100

.0

21.

6 #D

IV/0

! 0

.9

0.8

2

.6

2.8

7

7.5

113

.1

0.2

0

.4

DCB

Bank

Finan

cials

182

5

1,83

6 1

0,48

6 1

2,40

3 4

,146

4

,814

2

,076

2

,458

7

8

6

.7

8.8

2

4.9

22.

9 2

.7

2.2

1

2.5

10.

8 1

1.0

10.

6 1

.0

1.0

AXIS

Ban

kFin

ancia

ls 4

92

1,1

78,5

97

293

,256

2

96,0

43

173

,334

1

59,6

30

30,

300

45,

498

13

19

-63.

3 4

9.4

38.

9 2

6.0

0.4

0

.4

6.8

7

.4

5.6

8

.2

0.6

0

.8

Cana

ra B

ank

Finan

cials

326

1

94,7

46

172

,544

1

85,9

46

86,

732

91,

806

14,

816

24,

569

26

41

-149

.4

62.

1 1

2.7

7.9

6

.6

6.2

2

.2

2.1

5

.4

8.2

0

.3

0.4

Colg

ate

FMCG

1,0

12

275

,358

4

3,47

2 4

9,50

6 1

0,00

5 1

1,54

6 6

,010

6

,934

2

2 2

5 -1

.1

15.

4 4

5.8

39.

7 2

1.3

16.

9 2

7.2

23.

4 4

6.4

42.

6 5

2.0

47.

5

Baja

j Cor

pFM

CG 4

02

59,

361

8,7

09

9,6

31

2,6

92

2,9

79

2,4

38

2,6

31

17

18

0.2

7

.9

24.

4 2

2.6

12.

7 1

3.0

21.

8 1

9.8

52.

3 5

7.8

48.

5 5

7.0

Nestl

eFM

CG 6

,342

6

11,4

73

101

,096

1

12,7

42

21,

507

24,

159

12,

459

14,

162

129

1

47

17.

1 1

3.7

49.

1 4

3.2

18.

5 1

6.1

28.

3 2

4.7

37.

6 3

7.2

40.

5 3

9.7

Glax

o Sm

ithkl

ine

Con

FMCG

5,2

65

221

,439

3

9,74

2 4

2,70

3 8

,427

9

,403

7

,014

7

,747

1

67

184

-0

.7

10.

5 3

1.6

28.

6 8

.0

7.1

2

2.6

19.

7 2

5.3

24.

8 2

6.9

26.

3

ITCFM

CG 2

81

3,4

09,7

70

388

,213

4

27,3

04

149

,626

1

68,4

04

103

,012

1

14,8

30

9

10

9.6

1

1.5

32.

8 2

9.4

9.8

9

.3

22.

3 1

9.8

29.

8 3

1.7

23.

2 2

4.5

Godr

ej C

onsu

mer

Pro

FMCG

1,6

94

576

,824

1

01,1

71

112

,021

1

8,44

7 2

0,85

2 1

2,89

5 1

4,92

2 3

8 4

4 1

2.5

15.

7 4

4.7

38.

6 9

.5

8.0

3

2.1

28.

0 2

1.2

20.

7 1

6.5

17.

2

Dabu

r Ind

ia Lt

dFM

CG 2

92

514

,364

8

6,85

0 9

6,50

6 1

5,60

5 1

7,22

1 1

2,80

0 1

4,26

9 7

8

2

.2

12.

5 4

0.1

35.

7 1

0.5

9.1

3

2.9

29.

7 2

6.3

25.

4 2

4.3

23.

8

Brita

nnia

FMCG

3,3

81

405

,723

9

3,59

9 1

05,6

53

12,

116

14,

203

8,9

43

10,

404

75

87

9.6

1

6.3

45.

3 3

9.0

17.

5 1

3.7

33.

2 2

8.0

38.

6 3

5.2

40.

9 3

7.4

Apco

tex I

ndus

tries

FMCG

366

7

,588

5

,640

6

,557

7

98

1,0

74

500

6

91

24

33

30.

2 3

8.0

15.

2 1

1.0

3.4

2

.8

9.1

6

.0

22.

7 2

5.8

25.

0 2

8.7

Emam

iFM

CG 1

,018

2

31,0

98

28,

121

31,

637

8,0

47

9,1

98

5,6

02

6,4

66

25

28

5.8

1

5.4

41.

3 3

5.7

15.

7 1

4.2

29.

3 2

5.5

38.

1 3

9.8

18.

3 2

3.3

Jubi

lant

Food

work

sFM

CG 1

,032

6

8,05

9 2

6,18

7 2

9,23

1 2

,630

3

,018

8

89

1,1

02

14

17

-22.

4 2

3.9

76.

0 6

1.3

7.9

7

.0

25.

6 2

1.9

10.

4 1

1.4

10.

4 1

1.5

Asia

n Pa

ints

FMCG

1,0

60

1,0

16,7

02

164

,341

1

88,3

43

31,

859

35,

405

20,

334

22,

752

21

24

14.

3 1

1.9

50.

0 4

4.7

15.

4 1

3.2

31.

7 2

8.2

30.

8 2

9.6

31.

4 3

0.2

Agro

Tech

Food

sFM

CG 5

66

13,

781

8,0

66

8,5

85

651

7

69

316

4

21

13

17

35.

2 3

3.1

43.

6 3

2.7

3.8

3

.5

21.

8 1

8.2

8.7

1

0.7

8.2

8

.9

Mar

ico In

dustr

ies

FMCG

303

3

91,1

42

65,

107

73,

527

12,

389

14,

084

8,5

73

9,7

62

7

8

18.

3 1

3.9

45.

6 4

0.1

15.

5 1

3.0

31.

2 2

7.1

34.

0 3

2.5

31.

7 3

0.8

Hind

usta

n Un

ileve

rFM

CG 9

20

1,9

90,9

85

322

,609

3

63,0

26

65,

022

72,

675

42,

027

47,

864

19

22

2.5

1

3.9

47.

5 4

1.7

50.

4 4

5.7

30.

2 2

7.0

106

.1

109

.6

117

.2

121

.8

Hind

usta

n Co

nstru

ction

Infra

struc

ture

44

44,

521

36,

188

41,

616

4,3

43

4,9

94

-1,2

76

2,0

05

-1

2

-188

.3

-257

.1

-34.

9 2

2.2

1.7

1

.6

14.

8 1

1.4

-5.6

7

.3

4.7

7

.4

Page 40: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

41GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 40

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

NCC

Infra

struc

ture

97

53,

786

83,

510

94,

526

7,3

49

8,7

44

2,4

21

3,4

69

4

6

2.1

4

3.3

22.

2 1

5.5

1.5

1

.4

9.7

8

.2

6.7

8

.9

9.1

1

0.1

PNC

Infra

tech

Ltd

Infra

struc

ture

150

3

8,48

1 2

0,14

2 2

4,17

0 2

,618

3

,190

1

,971

1

,849

8

7

-1

7.7

-6.2

1

9.5

20.

8 2

.5

2.2

1

4.8

12.

1 1

3.6

11.

3 1

3.4

11.

1

Adan

i Por

ts &

SEZ

Infra

struc

ture

333

6

88,9

02

84,

450

94,

589

55,

535

62,

504

37,

017

41,

420

18

20

30.

0 1

1.9

18.

6 1

6.6

4.1

3

.3

16.

2 1

4.1

22.

1 2

0.1

11.

6 1

1.6

IRB

Infra

struc

ture

Infra

struc

ture

243

8

5,42

0 5

7,14

2 6

3,65

8 3

0,81

5 3

5,74

8 6

,734

6

,561

1

9 1

9 5

.9

-2.6

1

2.7

13.

0 1

.5

1.3

7

.8

6.8

1

1.5

9.9

3

.6

3.8

Asho

ka B

uild

con

Infra

struc

ture

209

3

9,11

4 3

0,06

6 3

5,08

9 8

,938

1

0,98

9 1

,087

1

,214

6

6

1

0.5

11.

6 3

6.0

32.

2 2

.0

1.9

9

.0

7.3

5

.5

5.9

5

.7

6.4

ITD C

emen

tatio

n In

frastr

uctu

re 1

80

27,

975

33,

059

38,

018

2,6

45

3,2

31

948

1

,291

6

8

9

7.1

36.

2 2

9.5

21.

7 4

.4

3.7

1

1.7

9.9

1

4.8

16.

9 1

5.0

16.

3

Ahlu

walia

Con

tracts

Infra

struc

ture

361

2

4,18

3 1

3,80

8 1

5,87

9 1

,864

2

,144

1

,001

1

,226

1

5 1

8 1

8.5

22.

6 2

4.2

19.

7 4

.8

4.0

1

3.2

11.

1 2

1.5

22.

0 2

0.0

20.

9

KNR

Cons

tructi

onIn

frastr

uctu

re 2

06

28,

967

14,

441

16,

607

2,0

94

2,4

08

1,5

24

1,6

29

11

12

-5.4

6

.9

19.

0 1

7.8

3.3

2

.8

14.

6 1

2.7

19.

1 1

7.2

16.

4 1

5.7

NIIT

Tech

nolo

gies

IT Se

rvice

s 4

30

26,

361

27,

710

30,

444

4,5

74

5,0

88

2,5

93

2,9

17

42

48

-3.1

1

2.4

10.

1 9

.0

1.5

1

.4

4.2

3

.4

15.

2 1

5.3

12.

9 1

5.0

Min

dtre

e Lt

dIT

Serv

ices

448

7

5,34

3 5

2,28

6 5

8,02

7 7

,116

8

,294

4

,107

5

,428

2

6 3

2 -1

9.4

23.

6 1

7.1

13.

9 2

.7

2.5

1

0.4

8.7

1

5.5

18.

3 1

7.3

19.

3

Wip

roIT

Serv

ices

500

1

,214

,730

5

48,2

81

578

,512

1

12,3

24

116

,869

8

3,19

9 8

9,68

2 3

4 3

7 -5

.5

8.3

1

4.6

13.

5 2

.4

2.2

1

1.9

11.

0 1

6.7

16.

1 1

5.9

15.

7

Pers

isten

t Sys

tem

sIT

Serv

ices

572

4

5,73

6 2

8,98

6 3

2,02

9 4

,585

5

,233

3

,099

3

,460

3

9 4

3 4

.2

11.

6 1

4.8

13.

2 2

.4

2.1

9

.7

8.4

1

6.2

16.

1 1

6.0

15.

8

KPIT

Tech

nolo

gies

IT Se

rvice

s 1

28

25,

230

33,

087

35,

534

3,6

28

4,2

82

2,1

96

2,5

93

11

14

-23.

9 1

8.1

11.

1 9

.4

1.5

1

.3

6.6

5

.2

13.

8 1

4.2

14.

4 1

2.9

Info

sys T

echn

olog

ies

IT Se

rvice

s 9

29

2,1

33,7

47

689

,083

7

71,2

03

187

,458

2

11,2

57

144

,440

1

64,4

49

63

72

7.0

1

3.9

14.

7 1

2.9

3.1

2

.8

9.3

8

.0

21.

2 2

1.3

22.

1 2

2.6

HCL T

echn

olog

ies

IT Se

rvice

s 8

19

1,1

69,0

35

467

,000

5

30,6

04

103

,070

1

14,7

65

81,

791

89,

906

58

63

50.

0 8

.8

14.

2 1

3.0

3.3

2

.9

11.

2 1

0.0

25.

5 2

5.2

25.

4 2

5.0

Tech

Mah

indr

aIT

Serv

ices

423

4

12,1

88

293

,050

3

20,7

68

44,

036

50,

112

29,

803

32,

613

34

37

-2.6

9

.4

12.

4 1

1.4

2.4

2

.1

9.2

7

.8

19.

2 1

8.4

15.

3 1

4.9

Tata

Con

sulta

ncy

IT Se

rvice

s 2

,321

4

,572

,674

1

,188

,280

1

,295

,824

3

26,8

28

343

,999

2

64,9

02

275

,357

1

34

140

9

.4

3.9

1

7.3

16.

6 5

.5

4.7

1

3.9

13.

0 3

2.0

28.

3 3

3.0

29.

6

Navk

ar

Logi

stics

212

3

0,24

7 3

,875

7

,048

1

,458

2

,710

8

96

1,6

64

6

12

-19.

8 8

5.8

33.

8 1

8.2

2.2

1

.9

23.

3 1

2.3

6.4

1

0.3

5.8

9

.8

Gate

way D

istrip

acks

Logi

stics

278

3

0,21

6 1

0,90

2 1

2,34

2 2

,411

3

,262

1

,081

1

,782

1

0 1

6 -1

.3

64.

9 2

7.9

16.

9 3

.1

2.9

1

4.9

11.

0 1

1.3

17.

2 8

.3

11.

9

Allca

rgo

Logi

stics

Logi

stics

174

4

3,91

5 5

6,67

4 6

1,74

0 4

,788

5

,943

2

,248

3

,007

9

1

2 -1

9.2

33.

7 1

9.5

14.

6 2

.5

2.2

1

0.1

8.1

1

3.0

15.

3 9

.3

12.

7

Cont

aine

r Cor

p Of

Indi

aLo

gisti

cs 1

,199

2

92,1

32

54,

668

60,

835

10,

442

11,

715

7,3

22

8,1

36

38

42

-7.0

1

1.1

31.

9 2

8.7

2.7

2

.6

27.

6 2

4.6

8.6

9

.0

8.4

8

.8

VRL L

ogist

ics Lt

d Lo

gisti

cs 3

46

31,

561

18,

056

19,

661

2,3

35

2,6

57

836

1

,042

9

1

1 -1

8.3

24.

7 3

7.8

30.

3 5

.8

5.4

1

4.4

12.

5 1

5.4

17.

8 1

1.1

13.

2

Orte

l Com

mun

icatio

nM

edia

115

3

,477

2

,533

3

,025

8

44

1,0

84

125

8

8 4

3

4

.2

-29.

9 2

7.7

39.

5 2

.3

2.2

6

.2

4.8

8

.3

5.5

8

.5

8.1

HT M

edia

Med

ia 8

4 1

9,63

2 2

7,31

1 2

9,52

0 3

,781

4

,329

2

,310

2

,750

1

0 1

2 3

2.6

19.

0 8

.5

7.1

0

.8

0.7

6

.7

5.1

9

.9

10.

4 9

.1

9.3

Hind

usta

n M

edia

Vent

Med

ia 2

93

21,

490

9,3

43

10,

320

1,9

13

2,3

20

1,8

24

2,1

39

25

29

0.7

1

7.3

11.

8 1

0.0

2.0

1

.7

11.

0 8

.3

16.

9 1

6.7

19.

2 1

8.8

Page 41: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

41GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 40

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

DB C

orp

Limite

dM

edia

380

6

9,86

2 2

2,76

1 2

5,19

6 6

,484

7

,586

3

,814

4

,690

2

1 2

6 2

8.3

23.

0 1

8.3

14.

9 4

.6

4.0

1

0.5

8.7

2

5.0

26.

8 2

2.5

24.

6

Dish

TVM

edia

100

1

06,9

67

30,

446

34,

089

10,

324

12,

614

2,7

29

3,8

44

3

4

-61.

3 4

0.9

39.

2 2

7.8

16.

1 1

0.2

10.

5 8

.4

41.

1 3

6.7

51.

3 4

0.1

Zee

Ente

rtain

men

tM

edia

537

5

16,0

97

65,

355

67,

083

17,

749

22,

115

10,

784

15,

312

11

16

18.

1 4

2.0

47.

8 3

3.7

7.4

4

.9

27.

9 2

0.8

15.

4 1

4.7

17.

4 1

8.2

Jagr

an P

raka

shan

Med

ia 1

97

64,

402

22,

853

24,

721

6,2

65

7,0

84

3,6

56

4,2

66

12

13

11.

4 1

6.7

17.

1 1

4.6

3.3

2

.8

10.

4 8

.8

19.

1 1

9.3

15.

8 1

5.6

Tata

Ste

elM

etal

s 4

57

444

,234

1

,131

,725

1

,233

,158

1

48,4

44

191

,073

2

5,03

1 6

0,51

2 2

6 6

2 1

70.1

1

41.8

1

7.8

7.3

1

.5

1.3

8

.5

6.3

8

.4

17.

3 4

.3

6.6

Hind

alco

Inds

Met

als

188

4

21,3

95

1,0

06,1

28

1,0

72,5

13

128

,588

1

37,8

86

28,

502

34,

367

14

17

265

.5

20.

6 1

3.6

11.

3 0

.9

0.9

7

.9

7.0

6

.9

7.8

5

.2

5.4

Veda

nta L

tdM

etal

s 2

35

695

,814

7

28,0

43

905

,686

2

15,2

76

272

,640

6

2,91

3 1

03,5

28

21

28

101

.1

31.

3 1

1.1

8.4

1

.4

1.1

6

.4

4.7

1

2.8

12.

7 8

.5

10.

4

NALC

O M

etal

s 6

7 1

30,1

83

72,

858

86,

399

10,

387

18,

962

6,6

36

12,

333

3

6

30.

6 8

5.8

19.

6 1

0.6

1.3

1

.2

10.

0 5

.3

6.5

1

1.2

4.7

1

0.0

SAIL

Met

als

61

252

,555

4

44,6

52

528

,855

1

1,28

5 4

6,87

4 -2

1,68

5 -3

,237

-5

-1

-4

7.4

-85.

1 -1

1.6

-78.

0 0

.7

0.7

5

3.8

13.

3 -5

.9

-0.9

-1

.1

1.6

JSW

Ste

elM

etal

s 1

91

460

,601

5

60,4

81

617

,282

1

25,2

34

139

,556

3

6,02

4 4

4,65

2 1

5 1

8 1

60.4

2

3.9

12.

8 1

0.3

2.2

1

.8

7.1

6

.1

16.

9 1

7.6

8.9

9

.4

Hind

usta

n Zi

ncM

etal

s 2

84

1,1

99,9

91

172

,674

2

12,3

35

96,

656

128

,835

8

2,29

8 1

10,9

86

19

26

0.4

3

4.9

14.

6 1

0.8

2.8

2

.4

9.5

6

.4

19.

3 2

2.3

19.

4 2

2.4

PEBS

Mid

cap

143

4

,886

5

,154

6

,278

6

57

861

2

81

400

8

1

2 -1

2.3

42.

6 1

7.4

12.

2 2

.1

1.9

9

.1

7.1

1

2.2

15.

3 1

2.9

14.

3

KDDL

Mid

cap

210

2

,273

4

,760

5

,513

2

96

459

3

6 9

8 3

9

-3

1.7

170

.6

62.

8 2

3.2

2.2

1

.9

11.

6 7

.4

3.5

8

.4

4.8

7

.2

Penn

ar In

ds.

Mid

cap

52

6,2

58

15,

320

19,

035

1,7

77

2,2

78

488

7

49

4

6

11.

4 5

3.3

12.

8 8

.4

1.1

1

.0

4.9

3

.9

8.9

1

2.4

12.

9 1

5.1

Praj

Inds

.M

idca

p 8

2 1

4,78

6 9

,089

1

1,26

4 6

37

1,4

31

409

9

67

2

5

-40.

2 1

36.4

3

5.7

15.

1 2

.3

2.2

2

2.3

10.

1 6

.5

14.

5 6

.1

14.

1

Sint

ex In

dustr

ies

Mid

cap

114

5

9,98

8 8

3,70

2 9

9,49

4 1

4,45

5 1

7,54

0 5

,209

6

,706

1

0 1

3 -3

0.0

28.

7 1

1.4

8.9

0

.9

0.8

8

.4

7.2

8

.1

9.5

5

.4

5.9

Gulf

Oil L

ubric

ants

Oil &

Gas

744

3

6,93

4 1

1,16

8 1

2,74

2 1

,803

2

,116

1

,187

1

,415

2

4 2

9 1

8.4

19.

2 3

1.1

26.

1 1

1.6

9.2

2

0.3

17.

2 3

7.4

35.

4 2

7.9

28.

8

Castr

ol In

dia

Oil &

Gas

432

2

13,7

00

36,

836

40,

418

10,

985

12,

207

7,4

12

8,2

41

15

17

13.

6 1

1.2

28.

8 2

5.9

31.

9 2

8.4

18.

6 1

6.7

110

.6

109

.5

129

.7

130

.2

Guja

rat S

tate

Pet

rone

tOi

l & G

as 1

85

104

,264

1

0,51

7 1

2,19

0 9

,127

1

0,69

8 4

,931

5

,998

9

1

1 1

0.9

21.

7 2

1.1

17.

4 2

.4

2.2

1

1.6

9.6

1

1.4

12.

5 9

.3

10.

4

Petro

net L

NGOi

l & G

as 4

53

339

,938

2

60,0

10

321

,633

2

4,03

1 2

9,82

8 1

4,56

5 1

7,66

6 1

9 2

4 3

6.2

21.

3 2

3.3

19.

2 4

.6

3.9

1

4.2

11.

2 1

9.6

20.

3 1

4.1

15.

9

GUJA

RAT G

AS LT

DOi

l & G

as 8

50

117

,040

5

0,87

2 5

5,77

4 7

,677

1

0,62

3 2

,245

4

,304

1

6 3

1 1

3.1

91.

7 5

2.1

27.

2 5

.1

4.5

1

8.1

12.

9 9

.9

16.

5 6

.4

9.1

GUJA

RAT G

AS LT

DOi

l & G

as 8

50

117

,040

5

0,87

2 5

5,77

4 7

,677

1

0,62

3 2

,245

4

,304

1

6 3

1 1

3.1

91.

7 5

2.1

27.

2 5

.1

4.5

1

8.1

12.

9 9

.9

16.

5 6

.4

9.1

Indr

apra

stha G

asOi

l & G

as 1

,072

1

50,0

66

37,

965

37,

552

10,

040

10,

899

5,7

90

6,5

68

43

47

38.

5 1

0.3

25.

2 2

2.8

5.3

4

.5

14.

1 1

2.7

21.

0 1

9.9

17.

8 1

7.5

Relia

nce

Indu

strie

sOi

l & G

as 1

,382

4

,491

,879

3

,079

,673

3

,807

,884

4

62,0

12

565

,352

2

84,3

44

224

,753

9

6 7

6 4

.4

-21.

1 1

4.3

18.

2 1

.5

1.4

1

4.2

12.

8 1

0.6

7.8

6

.7

5.2

Divi'

s Lab

orat

orie

sPh

arm

a 6

34

168

,320

4

4,13

1 4

1,44

4 1

6,11

7 1

3,79

1 1

1,87

0 9

,584

4

5 3

6 9

.2

-19.

3 1

4.2

17.

6 3

.3

2.9

1

0.4

12.

2 2

3.0

16.

5 -

-

Page 42: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

43GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 42

Phill

ipC

apita

l Ind

ia C

over

age

Uni

vers

e: V

alua

tio

n Su

mm

ary

CMP

Mkt

Cap

Ne

t Sal

es (R

s mn)

EB

IDTA

(Rs

mn)

PAT (

Rs m

n)EP

S (R

s)

EPS

Grow

th (%

) P

/E (x

) P

/B (x

) EV

/EBI

TDA

(x)

ROE

(%)

ROCE

(%)

Nam

e of

com

pany

Sect

orRs

Rs b

nFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

EFY

17E

FY18

E

Auro

bind

o Ph

arm

aPh

arm

a 6

43

376

,722

1

54,5

69

180

,376

3

7,09

7 4

5,81

5 2

3,75

9 2

9,25

3 4

1 5

0 1

6.5

23.

1 1

5.8

12.

8 4

.1

3.2

1

1.0

8.8

2

6.0

24.

9 2

4.5

24.

3

Glen

mar

k Pha

rma

Phar

ma

910

2

56,7

17

91,

779

101

,909

2

2,88

4 2

4,73

3 1

3,05

2 1

5,32

2 4

6 5

4 4

1.9

17.

4 1

9.7

16.

8 4

.7

3.7

1

2.5

11.

3 2

3.7

22.

0 1

6.3

16.

7

Lupi

nPh

arm

a 1

,428

6

44,8

07

171

,486

1

94,1

01

47,

459

53,

237

28,

598

33,

907

63

75

29.

2 1

8.6

22.

5 1

9.0

4.8

3

.9

14.

3 1

2.4

21.

3 2

0.6

- -

Sun

Phar

ma

Phar

ma

648

1

,554

,942

3

13,3

72

339

,916

1

06,6

40

118

,461

6

9,69

0 7

7,22

7 2

9 3

2 2

0.4

10.

8 2

2.3

20.

1 4

.3

3.6

1

3.3

11.

5 1

9.1

17.

9 1

5.7

15.

4

Dr R

eddy

's La

bs.

Phar

ma

2,6

24

434

,699

1

41,7

92

156

,917

2

7,64

9 3

6,87

5 1

3,79

3 2

1,18

4 8

1 1

24

-31.

7 5

3.6

32.

4 2

1.1

3.7

3

.2

16.

7 1

2.2

11.

3 1

5.1

7.0

1

0.7

Cadi

la H

ealth

care

Phar

ma

451

4

61,2

98

94,

489

116

,314

1

9,79

5 2

6,57

9 1

3,25

1 1

8,27

6 1

3 1

8 -1

0.0

37.

9 3

4.8

25.

2 7

.3

5.9

2

3.9

17.

7 1

9.9

22.

4 1

4.3

17.

0

Ipca

Labo

rato

ries

Phar

ma

599

7

5,55

1 3

1,51

6 3

7,39

7 4

,712

6

,900

1

,962

3

,898

1

6 3

1 4

4.0

98.

7 3

8.2

19.

2 3

.0

2.6

1

6.9

11.

4 7

.9

13.

6 6

.3

11.

4

Cipl

a Ltd

Ph

arm

a 5

72

460

,341

1

4,88

9 1

7,11

6 3

,871

4

,621

1

,369

1

,832

1

7 2

3 -1

2.7

33.

9 3

3.6

25.

1 3

.5

3.1

1

20.0

1

00.4

2

0.3

22.

2 -

-

Bioc

onPh

arm

a 1

,119

2

23,7

00

39,

924

47,

040

9,8

30

10,

405

6,1

96

5,5

53

31

28

37.

4 -1

0.4

36.

1 4

0.3

4.7

4

.3

23.

2 2

2.1

12.

6 1

0.2

11.

7 1

0.0

Titan

Com

pany

Reta

il 4

81

426

,892

1

28,3

90

146

,821

1

1,98

6 1

4,27

1 7

,785

9

,640

9

1

1 1

2.9

23.

8 5

4.8

44.

3 1

0.0

8.7

3

5.5

29.

5 2

0.1

21.

0 2

0.7

21.

6

Meg

hman

i Org

anics

Spec

ialty

Che

42

10,

554

15,

491

17,

440

3,0

05

3,5

75

880

1

,136

3

4

6

.6

29.

1 1

2.0

9.3

1

.4

1.3

5

.0

4.0

1

2.0

13.

6 1

0.6

12.

3

Cam

lin Fi

ne S

cienc

esSp

ecia

lty C

he 9

6 1

0,00

3 5

,251

7

,606

5

70

1,2

17

24

533

0

5

-9

4.5

414

.8

18.

7 4

.3

3.6

2

0.9

9.8

3

.5

20.

4 -

-

Aarti

Indu

strie

sSp

ecia

lty C

he 7

97

65,

458

29,

884

35,

607

6,5

15

7,9

40

3,2

53

4,1

08

40

50

26.

6 2

6.3

20.

1 1

5.9

5.2

4

.2

12.

2 1

0.0

27.

1 2

7.2

- -

SRF L

tdSp

ecia

lty C

he 1

,717

9

8,60

2 4

9,38

3 5

5,04

0 1

0,00

0 1

1,83

4 4

,730

5

,647

8

2 9

8 9

.1

19.

4 2

0.8

17.

5 3

.2

2.8

1

2.0

10.

2 1

5.4

15.

8 9

.4

10.

4

Vina

ti Or

gani

csSp

ecia

lty C

he 8

16

42,

101

7,1

67

8,3

79

2,1

57

2,6

09

1,3

56

1,6

70

26

32

41.

3 2

3.1

31.

0 2

5.2

6.5

5

.3

19.

4 1

6.8

20.

8 2

1.0

- -

Atul

Ltd

Spec

ialty

Che

2,4

50

72,

670

28,

860

32,

128

5,1

95

5,9

76

2,9

82

3,5

07

100

1

18

10.

7 1

7.6

24.

4 2

0.7

4.7

3

.9

14.

0 1

1.7

19.

4 1

8.9

- -

Bhar

ti In

frate

lTe

leco

m 3

50

646

,993

8

4,73

2 8

8,52

9 5

8,94

2 6

1,50

2 2

6,39

8 2

8,60

9 1

4 1

5 1

3.5

8.4

2

4.5

22.

6 3

.9

3.8

1

0.0

9.3

1

5.7

16.

6 1

1.8

12.

8

Bhar

ti Ai

rtel

Tele

com

342

1

,365

,312

9

90,3

57

1,0

63,6

83

349

,654

3

78,0

37

37,

404

57,

520

9

14

-4.2

5

3.8

36.

5 2

3.8

2.0

1

.8

7.3

6

.8

5.4

7

.5

5.5

5

.9

Tata

Com

mun

icatio

nsTe

leco

m 7

14

203

,362

2

20,4

47

237

,790

3

6,11

5 4

0,38

6 1

,401

3

,882

5

1

4 -3

5.7

177

.1

145

.2

52.

4 -3

9.6

-75.

7 7

.8

6.7

-2

7.3

-144

.5

4.8

6

.6

Idea

Cel

lula

rTe

leco

m 8

5 3

06,4

53

365

,055

3

67,3

34

107

,246

9

1,94

5 -4

,173

-2

7,80

5 -1

-8

-1

13.6

5

66.4

-7

3.4

-11.

0 1

.2

1.4

6

.9

8.8

-1

.7

-12.

5 2

.3

-0.1

Sour

ce: P

hilli

pCap

ital I

ndia

Res

earc

h Es

timat

es

Page 43: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

43GROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 42

Disclosures and Disclaimers

PhillipCapital (India) Pvt. Ltd. has three independent equity research groups: Institutional Equities, Institutional Equity Derivatives and Private Client Group. This report has been prepared by Institutional Equities Group. The views and opinions expressed in this document may or may not match or may be contrary at times with the views, estimates, rating, target price of the other equity research groups of PhillipCapital (India) Pvt. Ltd.

This report is issued by PhillipCapital (India) Pvt. Ltd. which is regulated by SEBI. PhillipCapital (India) Pvt. Ltd. is a subsidiary of Phillip (Mauritius) Pvt. Ltd. References to "PCIPL" in this report shall mean PhillipCapital (India) Pvt. Ltd unless otherwise stated. This report is prepared and distributed by PCIPL for information purposes only and neither the information contained herein nor any opinion expressed should be construed or deemed to be construed as solicitation or as offering advice for the purposes of the purchase or sale of any security, investment or derivatives. The information and opinions contained in the Report were consid-ered by PCIPL to be valid when published. The report also contains information provided to PCIPL by third parties. The source of such information will usually be disclosed in the report. Whilst PCIPL has taken all reasonable steps to ensure that this information is correct, PCIPL does not offer any warranty as to the accuracy or completeness of such information. Any person placing reliance on the report to undertake trading does so entirely at his or her own risk and PCIPL does not accept any liability as a result. Securities and Derivatives markets may be subject to rapid and unexpected price movements and past performance is not necessarily an indication to future performance.

This report does not have regard to the specific investment objectives, financial situation and the particular needs of any specific person who may receive this report. Investors must undertake independent analysis with their own legal, tax and financial advisors and reach their own regarding the appropriateness of investing in any securities or investment strategies discussed or recommended in this report and should understand that statements regarding future prospects may not be realized. In no circumstances it be used or considered as an offer to sell or a solicitation of any offer to buy or sell the Securities mentioned in it. The information contained in the research reports may have been taken from trade and statistical services and other sources, which we believe are reliable. PhillipCapital (India) Pvt. Ltd. or any of its group/associate/affiliate companies do not guarantee that such information is accurate or complete and it should not be relied upon as such. Any opinions expressed reflect judgments at this date and are subject to change without notice

Important: These disclosures and disclaimers must be read in conjunction with the research report of which it forms part. Receipt and use of the research report is subject to all aspects of these disclosures and disclaimers. Additional information about the issuers and securities discussed in this research report is available on request.

Certifications: The research analyst(s) who prepared this research report hereby certifies that the views expressed in this research report accurately reflect the research analyst’s personal views about all of the subject issuers and/or securities, that the analyst have no known conflict of interest and no part of the research analyst’s compensation was, is or will be, directly or indirectly, related to the specific views or recommendations contained in this research report. The Research Analyst certifies that he /she or his / her family members does not own the stock(s) covered in this research report.

Independence: PhillipCapital (India) Pvt. Ltd. has not had an investment banking relationship with, and has not received any compensation for investment banking services from, the subject issuers in the past twelve (12) months, and PhillipCapital (India) Pvt. Ltd does not anticipate receiving or intend to seek compensation for investment banking services from the subject issuers in the next three (3) months. PhillipCapital (India) Pvt. Ltd is not a market maker in the securities mentioned in this research report, although it or its affiliates may hold either long or short positions in such securities. PhillipCapital (India) Pvt. Ltd does not hold more than 1% of the shares of the company(ies) covered in this report.

Suitability and Risks: This research report is for informational purposes only and is not tailored to the specific investment objectives, financial situation or par-ticular requirements of any individual recipient hereof. Certain securities may give rise to substantial risks and may not be suitable for certain investors. Each investor must make its own determination as to the appropriateness of any securities referred to in this research report based upon the legal, tax and accounting consid-erations applicable to such investor and its own investment objectives or strategy, its financial situation and its investing experience. The value of any security may be positively or adversely affected by changes in foreign exchange or interest rates, as well as by other financial, economic or political factors. Past performance is not

necessarily indicative of future performance or results.

Sources, Completeness and Accuracy: The material herein is based upon information obtained from sources that PCIPL and the research analyst believe to be reliable, but neither PCIPL nor the research analyst represents or guarantees that the information contained herein is accurate or complete and it should not be relied upon as such. Opinions expressed herein are current opinions as of the date appearing on this material and are subject to change without notice. Furthermore, PCIPL is under no obligation to update or keep the information current.

Copyright: The copyright in this research report belongs exclusively to PCIPL. All rights are reserved. Any unauthorized use or disclosure is prohibited. No reprinting or reproduction, in whole or in part, is permitted without the PCIPL’s prior consent, except that a recipient may reprint it for internal circulation only and only if it is reprinted in its entirety.

Caution: Risk of loss in trading/investment can be substantial and even more than the amount / margin given by you. Investment in securities market are sub-ject to market risks, you are requested to read all the related documents carefully before investing. You should carefully consider whether trading/investment is appropriate for you in light of your experience, objectives, financial resources and other relevant circumstances. PhillipCapital and any of its employees, directors, associates, group entities, or affiliates shall not be liable for losses, if any, incurred by you. You are further cautioned that trading/investments in financial markets are subject to market risks and are advised to seek independent third party trading/investment advice outside PhillipCapital/group/associates/affiliates/directors/employees before and during your trading/investment. There is no guarantee/as-surance as to returns or profits or capital protection or appreciation. PhillipCapital and any of its employees, directors, associates, and/or employees, directors, associates of PhillipCapital’s group entities or affiliates is not inducing you for trading/investing in the financial market(s). Trading/Investment decision is your sole responsibility. You must also read the Risk Disclosure Document and Do’s and Don’ts before investing.

Kindly note that past performance is not necessarily a guide to future performance.

For Detailed Disclaimer: Please visit our website www.phillipcapital.in

For U.S. persons only: This research report is a product of PhillipCapital (India) Pvt Ltd. which is the employer of the research analyst(s) who has prepared the research report. The research analyst(s) preparing the research report is/are resident outside the United States (U.S.) and are not associated persons of any U.S. regulated broker-dealer and therefore the analyst(s) is/are not subject to supervision by a U.S. broker-dealer, and is/are not required to satisfy the regulatory licensing requirements of FINRA or required to otherwise comply with U.S. rules or regulations regarding, among other things, communications with a subject com-pany, public appearances and trading securities held by a research analyst account.

This report is intended for distribution by PhillipCapital (India) Pvt Ltd. only to "Major Institutional Investors" as defined by Rule 15a-6(b)(4) of the U.S. Securities andExchange Act, 1934 (the Exchange Act) and interpretations thereof by U.S. Securities and Exchange Commission (SEC) in reliance on Rule 15a 6(a)(2). If the recipient of this report is not a Major Institutional Investor as specified above, then it should not act upon this report and return the same to the sender. Further, this report may not be copied, duplicated and/or transmitted onward to any U.S. person, which is not the Major Institutional Investor.

In reliance on the exemption from registration provided by Rule 15a-6 of the Exchange Act and interpretations thereof by the SEC in order to conduct certain business with Major Institutional Investors, PhillipCapital (India) Pvt Ltd. has entered into an agreement with a U.S. registered broker-dealer, Decker & Co, LLC. Transactions in securities discussed in this research report should be effected through Decker & Co, LLC or another U.S. registered broker dealer.

If Distribution is to Australian Investors

This report is produced by PhillipCapital (India) Pvt Ltd and is being distributed in Australia by Phillip Capital Limited (Australian Financial Services Licence No. 246827).

This report contains general securities advice and does not take into account your personal objectives, situation and needs. Please read the Disclosures and Dis-claimers set out above. By receiving or reading this report, you agree to be bound by the terms and limitations set out above. Any failure to comply with these terms and limitations may constitute a violation of law. This report has been provided to you for personal use only and shall not be reproduced, distributed or published by you in whole or in part, for any purpose. If you have received this report by mistake, please delete or destroy it, and notify the sender immediately.

Page 44: pg 32. INTERVIEW – Ms ANU ACHARYA pg 35. Indian …backoffice.phillipcapital.in/Backoffice/Researchfiles/PC... ·  · 2017-06-02View, we attempt an in ... involved. An example

PBGROUND VIEW GROUND VIEW 1 - 30 April 2017 1 - 30 April 2017 44

inh

ou

sed

esig

n.co

.in